{ "count" : 31042, "data" : [ { "id" : "6a305951f292fd229cf46ac2", "title" : "Staff Engineer, Agentic Productivity and Infrastructure", "company" : "HomeVision", "industry" : "Engineering", "salary" : { "min" : 175000.0, "max" : 250000.0, "currency" : "CAD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Staff Engineer, Agentic Productivity and Infrastructure in Toronto, Canada, adjusted for Lead seniority and FinTech industry in 2024-2025." }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-16T11:10:12.948", "fingerprint" : "134bf93bc122738afbb7c5f2b5f740ef3d97191a0ba36f950f1ddac00cfa6697", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/homevision/cfe075c2-3e1d-450d-950f-91d5651d04a5/application", "externalId" : "cfe075c2-3e1d-450d-950f-91d5651d04a5", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "43.6534817,-79.3839347" }, { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "Toronto, Ontario, Canada; San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Go, Python, TypeScript, LLMs, Agents, Infrastructure-as-Code, Terraform, Pulumi, Observability", "professionalSkills" : [ "System design", "Platform operations", "Developer experience", "Agent reliability", "AI-assisted operations" ], "hardSkillsList" : [ "Agentic workflows", "Automated workflows", "CI/CD", "Observability", "Alerting", "Incident response", "Internal developer platform", "Infrastructure-as-Code", "System health" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Agentic workflows", "level" : "intermediate" }, { "name" : "Automated workflows", "level" : "intermediate" }, { "name" : "CI/CD", "level" : "intermediate" }, { "name" : "Observability", "level" : "intermediate" }, { "name" : "Alerting", "level" : "intermediate" }, { "name" : "Incident response", "level" : "intermediate" }, { "name" : "Internal developer platform", "level" : "intermediate" }, { "name" : "Infrastructure-as-Code", "level" : "intermediate" }, { "name" : "System health", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Agentic Productivity, Infrastructure, Developer Tooling, Automation", "majorSkillsList" : [ "Agentic Productivity", "Infrastructure", "Developer Tooling", "Automation" ], "coreResponsibilities" : "Streamline build-and-ship loop, Design internal systems, Design agents, Accelerate code writing, Accelerate code review, Accelerate code testing, Accelerate code shipping, Automate platform operations, Build systems to keep platform healthy, Build CI/CD, Build observability, Build alerting, Build agent-assisted monitoring, Build agent-assisted incident response, Improve internal developer platform, Create paved roads, Create tooling, Create environments, Seek leverage, Identify automation payoff, Identify agent payoff, Prototype quickly, Measure impact on velocity, Measure impact on reliability, Elevate the team, Establish internal tooling patterns, Establish libraries, Establish standards, Mentor engineers, Recruit engineers", "teamCollaboration" : "Partner with CTO; Partner with engineering leadership; Engineering teammates; Cross-functional teams", "projectManagementSkills" : [ "Prototype quickly", "Measure impact" ], "domainKnowledge" : "Mortgage lending; AI underwriting; SDLC automation; Agentic developer tooling; Internal automation", "domainList" : [ "mortgage-lending", "ai-underwriting", "sdlc-automation", "agentic-developer-tooling", "internal-automation" ], "domainSpecificKnowledge" : [ "Mortgage lending", "AI underwriting", "SDLC automation", "Agentic developer tooling", "Internal automation" ], "toolProficiency" : [ "Terraform", "Pulumi" ], "communicationSkills" : "Communicate clearly", "continuousLearning" : "Continuous learning; Continuous improvement; Learning support; Professional development", "innovationCreativity" : "Prototype development", "problemSolvingSkills" : "Difficult systems problems", "outcomesObjectives" : "Make SDLC radically automated; Make platform operations radically automated; Ship and operate more than headcount suggests; Accelerate how we write code; Accelerate how we review code; Accelerate how we test code; Accelerate how we ship code; Turn manual toil into automated workflows; Keep platform healthy with less human effort; Let every engineer ship faster; Let every engineer ship safer; Make agentic workflows reliable; Make agentic workflows repeatable; Move team's velocity", "qualificationsBasic" : "Experience building developer tooling, Experience building internal platforms, Experience building CI/CD, Experience building DevOps/SRE systems, Hands-on experience building with LLMs, Hands-on experience building with agents, Comfort with infrastructure, Comfort with operations, Track record of leading technical surface end-to-end", "qualificationsPreferred" : "Proficiency in Go, Proficiency in Python, Proficiency in TypeScript, Conviction and curiosity about applying LLMs to engineering workflows, Conviction and curiosity about applying agents to engineering workflows, Experience with Infrastructure-as-Code, Experience with Terraform, Experience with Pulumi, Experience with observability, Experience with practices that keep systems healthy under load, Built agentic developer tooling, Built internal automation that measurably moved team's velocity", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "STAFF ENGINEER, AGENTIC PRODUCTIVITY & INFRASTRUCTURE Location: San Francisco - hybrid, in-office two days a week Compensation: Competitive base + leadership-level equity MAKE OUR ENGINEERING ORG AS AGENTIC AS OUR PRODUCT AI is transforming mortgage lending - and it’s transforming how software gets built. We build AI agents for our customers; we should be just as aggressive about using agents to build and operate HomeVision itself. The opportunity is to make our own software development lifecycle and platform operations radically more automated and agentic, so our small team can ship and operate far more than our headcount would suggest. WHO WE ARE HomeVision is the AI underwriting platform for the $13 trillion U.S. mortgage industry. Our platform, MIRA, has already automated more than two million appraisal reviews for many of the country’s largest lenders and appraisal management companies, reducing review time by 75% and doubling underwriter productivity. Now we’re expanding beyond appraisal review to cover the full underwriting workflow - income, assets, credit, collateral, and loan file decisioning - to create the first end-to-end AI underwriting platform for the industry. MIRA’s been adopted by dozens of real enterprise customers with contracted production demand, including Newrez, the fourth-largest mortgage lender in the U.S. and a strategic investor in HomeVision, alongside our venture backers, Initialized Capital and NVP Capital. We’re looking for a staff-level engineer to own internal infrastructure and agentic productivity - the tools, systems, and agents that make our SDLC and platform maintenance faster, safer, and more automated. This is a force-multiplier role for the entire engineering org. You’ll partner directly with our CTO and engineering leadership to decide where agents and automation create the most leverage, and then build it. WHAT YOU’LL DO - Streamline the build-and-ship loop. Design internal systems and agents that accelerate how we write, review, test, and ship code - turning manual engineering toil into automated, agent-assisted workflows. - Automate platform operations. Build the systems that keep the platform healthy with less human effort - CI/CD, observability, alerting, and agent-assisted monitoring and incident response. - Continually improve our internal developer platform. Create the paved roads, tooling, and environments that let every engineer ship faster and more safely, and that make our agentic workflows reliable and repeatable. - Seek leverage. Identify where automation and agents pay off most across the engineering org, prototype quickly, and measure the impact on velocity and reliability. - Elevate the team. Establish the internal tooling patterns, libraries, and standards the rest of the team builds against. Mentor and recruit the engineers who’ll work alongside you. WHO YOU ARE - You’re deeply customer-focused. But in this case, your “customers” are your engineering teammates. You care about their workflows and the outcomes your tools produce, and you measure success by how much faster and safer the org ships. - You’re a builder at heart. You’ve shipped meaningful systems used by real people. You likely have side projects, strong opinions about technology, and genuine curiosity about where AI is heading. You are a creator. - You operate with urgency and ownership. You move quickly without sacrificing reliability or trust. You proactively identify problems, communicate clearly, and drive solutions. - You elevate the people around you. You bring strong engineering judgment, high standards, and collaborative energy. Teams become stronger when you’re involved. - You’re excited by difficult systems problems. Developer experience, automation, agent reliability, observability, and AI-assisted operations genuinely interest you. WHAT YOU’LL BRING ON THE TECHNICAL SIDE - Strong proficiency in Go, Python, and/or TypeScript is a bonus, but we trust that great engineers can learn on the job. - Experience building developer tooling, internal platforms, CI/CD, or DevOps/SRE systems in production. - Hands-on experience building with LLMs or agents - or strong conviction and curiosity about applying them to engineering workflows. - Comfort with infrastructure and operations - Infrastructure-as-Code (Terraform/Pulumi), observability, and the practices that keep systems healthy under load. - A track record of leading a technical surface end-to-end. Bonus if you’ve built agentic developer tooling or internal automation that measurably moved a team’s velocity. HOW WE WORK We’re a hybrid team headquartered in San Francisco, with team concentrations in Seattle and Argentina, with other great team members in parts of the U.S. Our values are the ones we actually use: - Start with questions, not answers. - Run at problems - make your footprint bigger than your foot. - Continuous learning, continuous improvement. - Be transparent and collaborative. - Value time. - Play to win, win for everyone. - Always do the loving thing. We’re growing the engineering team meaningfully over the next twelve months and this role will have a direct hand in shaping who that team becomes. COMPENSATION AND BENEFITS - Competitive compensation calibrated to senior/principal-level engineers in San Francisco - Meaningful equity ownership - Full medical, dental, and vision coverage - 401(k) with company match - Flexible vacation policy - Parental leave - Learning and professional development support HOW TO APPLY Send a note, a résumé, and (ideally) links to things you’ve built. GitHub, side projects, products you’ve shipped - whatever lets us see how you think and build. We’re thoughtful and deliberate about who joins the team, but we move quickly when we find the right person.", "summaryDescription" : "Staff Engineer, Agentic Productivity and Infrastructure at HomeVision. Skills: Agentic Productivity, Infrastructure, Developer Tooling, Automation. Streamline build-and-ship loop. 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19 - Toronto Head Office (19 - Toronto Head Office)
150 King Street West
Suite 2200
Toronto, M5H 1J9

" ], "timestamp" : "2026-06-16T00:46:31.767", "fingerprint" : "85a7438bcb6e0f582a7f4f6eac15687d80a90b56d0fd5671355997c75f69e541", "source" : "taleo", "language" : "en", "applyUrl" : "https://iamgold.taleo.net/careersection/ex/jobdetail.ftl?job=57323", "externalId" : "57323", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Toronto", "state" : "Ontario", "country" : "Canada", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "43.6534817,-79.3839347" } ], "locationText" : "Toronto, Ontario, Canada", "experienceLevel" : "Manager", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "We are IAMGOLD. Innovative, Accountable Mining. IAMGOLD is a Canadian-based gold mining company with operations and development projects across North America and West Africa. With flagship operations like the Côté Gold Mine in Ontario, one of Canada’s largest and most technologically advanced gold mines, we’re not just mining gold; we’re redefining what mining means for the future. At IAMGOLD, we believe that when we engage, empower, and support each other, we create extraordinary outcomes—delivering value for our people, partners, and stakeholders while building stronger, more resilient communities. Recognized as one of the 2025 GTA Top Employers, we offer an environment designed for growth, world-class rewards, cutting-edge development programs, and a culture that values fresh ideas and collaboration. Our results speak for themselves: ranked 13th on the 2025 TSX30, we’ve proven that performance and purpose go hand in hand. Here, you’ll work on projects that matter, leveraging technology, sustainability, and creativity to deliver impact for our teams, communities, and the planet. Innovation drives us. Sustainability anchors us. Accountability shapes us. Want to Learn More About IAMGOLD? Check out the IAMGOLD Blog Read about our Sustainability Approach About the role: Join us as the Manager, Enterprise Technology , where you will lead the architecture, planning, implementation, and management of our global technology infrastructure. Reporting to the Senior Manager, Infrastructure and Operations, you will ensure our network, cloud, computing platforms, and communications systems are secure, resilient, and scalable. In this high‑impact role, your leadership will enable enterprise‑wide digital transformation, support critical business objectives, and drive operational excellence across the organization. Responsibilities: Develop and lead our global infrastructure strategy and technology roadmap. Oversee infrastructure operations to ensure reliability, high availability, and performance. Drive modernization initiatives, including cloud adoption, automation, and platform improvements. Strengthen infrastructure security and collaborate with cybersecurity teams on threat mitigation. Lead disaster recovery and business continuity planning and testing. Manage and mentor infrastructure and operations teams, fostering collaboration and continuous improvement. Build strong vendor and MSP partnerships; negotiate contracts and manage service performance. Oversee infrastructure budgets, forecasts, and reporting. Translate business requirements into secure, scalable, and effective technology solutions. Key Skills & Knowledge: 7+ years of experience in IT infrastructure leadership within complex, multi‑site environments. Strong knowledge of cloud platforms (Azure preferred), networking, architecture, and security. Proven success leading teams and large‑scale modernization or cloud migration initiatives. Experience in industrial or mining environments (IT + OT experience is a strong asset). We Value: Certifications such as ITIL, PMP, Azure, Cisco, or FortiGate are highly valued. Excellent communication, decision‑making, and stakeholder engagement skills. Ability to lead through change, develop talent, and build a culture of innovation and collaboration. Strength in budgeting, vendor management, and prioritization under pressure. What we Offer: At IAMGOLD, we don’t just reward performance we invest in your potential. Our total rewards package is designed to support your well-being today and encourage your growth for tomorrow. Because the future of mining, and your career, starts here. • Comprehensive Health Coverage – Extended health, dental, and insurance benefits for peace of mind. • Flexible Spending Power – Health & Personal Spending Accounts to fit your evolving needs. • Support When It Matters – Employee & Family Assistance Program for life’s challenges. • Work-Life Balance – Summer Hours and an End-of-Year Office Closure to recharge and refocus. • Flexibility Built In – Hybrid work model and adaptable arrangements for the future of work. • Future-Ready Savings – Registered Pension Plan with company match, plus TFSA & RRSP options. • Shared Success – Employee Share Purchase Plan with company match—because we grow together. • Career Growth That Counts – Coaching for success, online learning, and conferences to keep you ahead of the curve. • Culture That Connects – Town halls, lunch & learns, and collaborative spaces where ideas shape tomorrow. We recognize that not everyone will meet every requirement listed, and that’s okay. If this role excites you and you believe you have relevant experience or transferable skills, we encourage you to apply. We value potential and are committed to supporting growth and development. We’re an equal opportunity employer, committed to building a workplace where every perspective sparks progress. We welcome applications from women, Indigenous Peoples, visible minorities, persons with disabilities, and members of the 2SLGBTQIA+ community. Need accommodation during the recruitment process? Just let us know, we’ll make it happen. Mining. Redefined. Be part of a modern company driven by innovation, accountability, and sustainability. Apply Today! Please note that IAMGOLD does not use AI tools within our applicant tracking system to support the screening of applications. Canada", "summaryDescription" : "Manager, Enterprise Technology Infrastructure at IAMGOLD", "createdAt" : "2026-06-14T18:49:45.938", "lastUpdated" : "2026-06-16T00:46:31.767", "ingestTimestamp" : "2026-06-14T18:49:45.938", "mongoId" : "69ce5e199bc74574cb674d3a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ ], "skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Manager", "dataQualityScore" : 0.6666667, "_score" : 895.99255, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Mining", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6ace74d8ee00a090e131", "title" : "Agentic AI Engineer", "company" : "Innodata Inc.", "industry" : "Technology", "salary" : { "min" : 100000.0, "max" : 120000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "INN - Remote - US", "locations" : [ "INN - Remote - US" ], "timestamp" : "2026-06-15T12:24:10.013", "fingerprint" : "b5cc7c7e35a305974a3c7f7f12908b6fac3bb2a43afdfbe62264ece7202dbccf", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/innodatainc/jobs/4272039009", "externalId" : "4272039009", "industryFunction" : { }, "structuredLocations" : [ { "country" : "United States", "continent" : "na", "workMode" : "remote" } ], "locationText" : "United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Python, PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, AutoGen, FastAPI, Flask, Node.js, REST APIs, GraphQL APIs, Microservices, ETL, SQL, NoSQL, Vector DBs, Docker, Kubernetes, CI/CD, AWS, GCP, Azure", "professionalSkills" : [ "System design", "Backend development", "API development", "Data pipeline development", "Containerization", "Deployment", "Monitoring", "Observability", "Drift detection" ], "hardSkillsList" : [ "Fine-tuning techniques", "Agent-to-agent orchestration", "Multi-context protocol", "Retrieval-augmented generation", "Data governance", "Bias mitigation", "Lineage tracking" ], "hardSkills" : [ { "name" : "Fine-tuning techniques", "level" : "intermediate" }, { "name" : "Agent-to-agent orchestration", "level" : "intermediate" }, { "name" : "Multi-context protocol", "level" : "intermediate" }, { "name" : "Retrieval-augmented generation", "level" : "intermediate" }, { "name" : "Data governance", "level" : "intermediate" }, { "name" : "Bias mitigation", "level" : "intermediate" }, { "name" : "Lineage tracking", "level" : "intermediate" } ], "majorSkills" : "Agentic AI, Multi-agent systems, Foundation models, RAG pipelines", "majorSkillsList" : [ "Agentic AI", "Multi-agent systems", "Foundation models", "RAG pipelines" ], "coreResponsibilities" : "Design multi-agent systems, Build multi-agent systems, Deploy multi-agent systems, Architect agent-to-agent orchestration pipelines, Fine-tune foundation models, Integrate RAG pipelines, Build A2A orchestration, Implement MCP for context reuse, Implement MCP for collaboration, Develop APIs, Develop backend services, Integrate with enterprise systems, Build secure data pipelines, Ensure data governance, Ensure bias mitigation, Ensure lineage tracking, Containerize agents, Deploy agents, Monitor agents, Benchmark accuracy, Benchmark safety, Benchmark compliance", "teamCollaboration" : "Collaborate with QA; Collaborate with red teaming; Collaborate with product leads", "projectManagementSkills" : [ "CI/CD pipelines" ], "domainKnowledge" : "Enterprise automation; Generative AI; AI systems; Foundation models; Retrieval-augmented generation; Agent-to-agent communication; Multi-context protocol", "domainList" : [ "enterprise-automation", "generative-ai", "ai-systems", "foundation-models", "retrieval-augmented-generation", "agent-to-agent-communication", "multi-context-protocol" ], "domainSpecificKnowledge" : [ "Enterprise automation", "Generative AI", "AI systems", "Foundation models", "Retrieval-augmented generation", "Agent-to-agent communication", "Multi-context protocol" ], "toolProficiency" : [ "LangChain", "LangGraph", "CrewAI", "AutoGen", "Pinecone", "Weaviate", "FAISS", "Milvus", "Jenkins", "GitHub Actions" ], "innovationCreativity" : "Frontier of agentic AI", "qualificationsBasic" : "Advanced proficiency in Python, Proficiency in PyTorch/TensorFlow, Proficiency in Hugging Face, Hands-on experience with LangChain/LangGraph, Hands-on experience with MCP, Hands-on experience with A2A orchestration, Hands-on experience with multi-agent architectures, Proficient in ETL pipelines, Proficient in SQL/NoSQL, Proficient in vector DBs, Backend expertise in FastAPI/Flask/Node.js, Backend expertise in REST/GraphQL APIs, Backend expertise in microservices, DevOps/MLOps experience, Cloud experience with AWS/GCP/Azure AI services, Secure integration practices", "qualificationsPreferred" : "Familiarity with enterprise HR/ATS systems, Familiarity with workflow automation", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: We are seeking an Agentic AI Engineer to design, build, and deploy sophisticated multi-agent AI systems that operate autonomously across complex enterprise environments. You will architect agent-to-agent orchestration pipelines, fine-tune foundation models, and integrate retrieval-augmented generation (RAG) into scalable backend infrastructure — bridging the gap between cutting-edge AI research and real-world production deployment. This is a high-impact role at the frontier of agentic AI, building the intelligent systems that will define the next generation of enterprise automation. What You’ll Own: Design and implement multi-agent systems using LangChain, LangGraph, CrewAI, AutoGen or similar frameworks. Build A2A (agent-to-agent) orchestration and implement MCP (multi-context protocol) for context reuse and collaboration. Fine-tune foundation models (LoRA, RLHF, DPO) and integrate retrieval-augmented generation (RAG) pipelines. Develop APIs and backend services (FastAPI/Flask/Node.js) and integrate with enterprise systems (HRIS, CRM, ERP). Build secure data pipelines (ETL, embeddings, vector DB ingestion) and ensure governance, bias mitigation, and lineage. Containerize, deploy, and monitor agents (Docker, Kubernetes, CI/CD pipelines) with observability and drift detection. Collaborate with QA, red teaming, and product leads to benchmark accuracy, safety, and compliance. You’ll Thrive in This Role If You Have: Advanced proficiency in Python, PyTorch/TensorFlow, Hugging Face, and fine-tuning techniques (LoRA, RLHF). Hands-on experience with LangChain/LangGraph, MCP, A2A orchestration, and multi-agent architectures. Proficient in ETL pipelines, SQL/NoSQL, vector DBs (Pinecone, Weaviate, FAISS, Milvus). Backend expertise in FastAPI/Flask/Node.js, REST/GraphQL APIs, and microservices. DevOps/MLOps experience: Docker, Kubernetes, CI/CD (Jenkins/GitHub Actions), monitoring/observability. Cloud experience with AWS/GCP/Azure AI services and secure integration practices. Bonus: familiarity with enterprise HR/ATS systems (Workday, SAP, Paychex) and workflow automation. The expected salary range for this position is $100,000 – $120,000 USD per year, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams. If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov.", "summaryDescription" : "Agentic AI Engineer at Innodata Inc.. Skills: Agentic AI, Multi-agent systems, Foundation models, RAG pipelines. Design multi-agent systems. Build multi-agent systems", "postedDate" : "2026-06-14T09:29:20.191", "createdAt" : "2026-06-14T09:29:20.191", "lastUpdated" : "2026-06-15T12:24:10.013", "ingestTimestamp" : "2026-06-14T09:29:20.191", "mongoId" : "6a2c6ace74d8ee00a090e131", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 100000, "salaryAnnualMax" : 120000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Fine-tuning techniques", "Agent-to-agent orchestration", "Multi-context protocol", "Retrieval-augmented generation", "Data governance", "Bias mitigation", "Lineage tracking", "Agentic AI", "Multi-agent systems", "Foundation models", "RAG pipelines", "System design", "Backend development", "API development", "Data pipeline development", "Containerization", "Deployment", "Monitoring", "Observability", "Drift detection", "CI/CD pipelines", "Enterprise automation", "Generative AI", "AI systems", "Agent-to-agent communication", "LangChain", "LangGraph", "CrewAI", "AutoGen", "Pinecone", "Weaviate", "FAISS", "Milvus", "Jenkins", "GitHub Actions" ], "skillCount" : 35, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 826.5715, "daysOld" : 1, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "68e0a7e1ce260f92cbf8e939", "title" : "Software Development Manager, Enterprise Infrastructure and Identity Services", "company" : "Amazon.com Services LLC", "industry" : "Software Development, amazon security", "salary" : { "min" : 166400.0, "max" : 287700.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Bellevue, Washington, USA", "locations" : [ "Bellevue, Washington, USA" ], "timestamp" : "2026-06-15T04:26:07.722", "fingerprint" : "a4d4e10c2e872178af03adb0a9b9fd6c292a90832e777c33e32eb4be969f082c", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3101260/apply", "externalId" : "4a267fc6-6799-42e8-80aa-e81af9fde144", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bellevue", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6144219,-122.1923370" } ], "locationText" : "Bellevue, Washington, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "Cloud, Devices, Retail, Entertainment, Healthcare, Operations, Physical stores", "professionalSkills" : [ "System design", "Technical designs" ], "hardSkillsList" : [ "Software development", "DevOps", "Cloud engineering", "AI/ML", "Data engineering", "Security engineering", "Automation" ], "softSkillsList" : [ "Leadership", "Mentoring" ], "hardSkills" : [ { "name" : "Software development", "level" : "intermediate" }, { "name" : "DevOps", "level" : "intermediate" }, { "name" : "Cloud engineering", "level" : "intermediate" }, { "name" : "AI/ML", "level" : "intermediate" }, { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "Security engineering", "level" : "intermediate" }, { "name" : "Automation", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Mentoring" } ], "majorSkills" : "Software development management, Enterprise infrastructure, Identity services, Security services", "majorSkillsList" : [ "Software development management", "Enterprise infrastructure", "Identity services", "Security services" ], "coreResponsibilities" : "Hire, motivate, mentor, and grow engineering team, Provide opportunities for career objectives, Collaborate with cross-functional teams, Work effectively with product managers and software engineers, Ensure timely execution of automation goals, Ensure timely execution of customer launches, Remove blockers, Reduce execution risks, Provide input on OP1, roadmaps, and strategic discussions, Architect technical designs, Develop technical designs, Build operational excellence, Reduce lead times, Maintain operations of critical services, Communicate technical decisions, Communicate progress", "teamCollaboration" : "Cross-functional teams; Product managers; Software engineers", "projectManagementSkills" : [ "Roadmaps", "Strategic discussions" ], "domainKnowledge" : "Enterprise infrastructure; Identity services; Security", "domainList" : [ "enterprise-infrastructure", "identity-services", "security" ], "domainSpecificKnowledge" : [ "Enterprise infrastructure", "Identity services", "Security" ], "communicationSkills" : "Technical decisions; Progress", "continuousLearning" : "Knowledge-sharing; Training; Career-advancing resources", "innovationCreativity" : "Inventing; Simplifying; Innovative ways; Disruptive innovations; Industry-leading innovations", "problemSolvingSkills" : "Solving security hurdles", "outcomesObjectives" : "Raise security bar; Deliver industry-best security services", "qualificationsBasic" : "3+ years engineering team management, 7+ years engineering experience, 8+ years leading definition and development of multi tier web services, Knowledge of engineering practices and patterns for full software/hardware/networks development life cycle, Experience partnering with product or program management teams", "qualificationsPreferred" : "Experience communicating with users, other technical teams, and senior leadership, Experience recruiting, hiring, mentoring/coaching and managing teams of Software Engineers, Experience designing or architecting new and existing systems, Master's degree in computer science, engineering, mathematics or equivalent", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "We are open to hiring candidates to work out of one of the following locations: Bellevue, WA USA Our team is looking for a highly motivated Software Development Manager (SDM) to lead a software development team in Amazon Security who will raise the security bar by delivering industry-best security services. You should be somebody who enjoys inventing and simplifying around complex security challenges, obsesses over the customer experience, and feels strongly about delivering results. You should be passionate about solving security hurdles in innovative ways. We do not desire to simply produce good software here at Amazon Security... we want to produce disruptive, industry-leading innovations. Key job responsibilities Key job responsibilities • Hire, motivate, mentor, and grow a high-performing engineering team, providing them with appropriate opportunities to succeed in their career objectives. • Collaborate with cross-functional teams: Work effectively with product managers and software engineers on other Commerce Platform teams to ensure the successful delivery of features. • Ensure timely execution of key organizational automation goals and customer launches by removing blockers and reducing execution risks. • Work closely with the leadership team to provide input on OP1, roadmaps, and strategic discussions. • Be deeply involved with engineers to architect and develop the best technical designs and approaches. • Build operational excellence to reduce lead times and maintain the operations of critical services. • Clearly communicate technical decisions and progress to both technical and non-technical audiences. About the team Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve. Basic Qualifications: - 3+ years of engineering team management experience - 7+ years of engineering experience - 8+ years of leading the definition and development of multi tier web services experience - Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations - Experience partnering with product or program management teams Preferred Qualifications: - Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy - Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers - Experience designing or architecting (design patterns, reliability and scaling) of new and existing systems - Master's degree in computer science, engineering, mathematics or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $166,400/year in our lowest geographic market up to $287,700/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Software Development Manager, Enterprise Infrastructure and Identity Services at Amazon.com Services LLC. Skills: Software development management, Enterprise infrastructure, Identity services, Security services. Hire, motivate, mentor, and grow engineering team. Provide opportunities for career objectives", "postedDate" : "2026-06-13T12:42:26.902", "createdAt" : "2026-06-13T12:42:26.902", "lastUpdated" : "2026-06-15T04:26:07.722", "ingestTimestamp" : "2026-06-13T12:42:26.902", "mongoId" : "68e0a7e1ce260f92cbf8e939", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3101260/apply", "salaryAnnualMin" : 166400, "salaryAnnualMax" : 287700, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Software development", "DevOps", "Cloud engineering", "AI/ML", "Data engineering", "Security engineering", "Automation", "Leadership", "Mentoring", "Software development management", "Enterprise infrastructure", "Identity services", "Security services", "System design", "Technical designs", "Roadmaps", "Strategic discussions", "Security" ], "skillCount" : 18, "jobCategory" : "engineering", "dataQualityScore" : 1.0, "_score" : 807.7802, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Security" }, { "id" : "6a2ca17574d8ee00a09a5954", "title" : "Research Engineer - Data Infrastructure", "company" : "Rhoda AI", "industry" : "Research", "salary" : { "min" : 185000.0, "max" : 265000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Research Engineer in the Technology industry in Palo Alto, USA, adjusted for company size and specific role responsibilities." }, "location" : "Palo Alto", "locations" : [ "Palo Alto" ], "timestamp" : "2026-06-16T06:05:20.878", "fingerprint" : "a7d2ce63b5b0739ffe98855ef0345f3066560a6653365cf95983eefecd99bb51", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/rhoda-ai/c90321f2-5085-4f99-ac13-0de996ba1dd1/application", "externalId" : "c90321f2-5085-4f99-ac13-0de996ba1dd1", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Palo Alto", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.4443293,-122.1598465" } ], "locationText" : "Palo Alto, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, Cloud object storage, Databases, Metadata stores, Ray, Spark, Vision-language models, Snowflake, BigQuery, Redshift, DVC, Delta Lake", "professionalSkills" : [ "System design", "ML infrastructure", "Data infrastructure", "Distributed systems", "Production reliability", "Performance optimization", "Cost efficiency" ], "hardSkillsList" : [ "Data pipeline optimization", "Storage system optimization", "Indexing systems", "Retrieval systems", "Dataset querying", "Dataset filtering", "Dataset iteration", "Observability frameworks", "Monitoring", "Alerting", "Failure recovery", "Workload balancing", "Data artifact management", "Data versioning", "Data lineage", "Reproducibility", "Traceability", "Data exploration", "Data analysis", "ML inference" ], "hardSkills" : [ { "name" : "Data pipeline optimization", "level" : "intermediate" }, { "name" : "Storage system optimization", "level" : "intermediate" }, { "name" : "Indexing systems", "level" : "intermediate" }, { "name" : "Retrieval systems", "level" : "intermediate" }, { "name" : "Dataset querying", "level" : "intermediate" }, { "name" : "Dataset filtering", "level" : "intermediate" }, { "name" : "Dataset iteration", "level" : "intermediate" }, { "name" : "Observability frameworks", "level" : "intermediate" }, { "name" : "Monitoring", "level" : "intermediate" }, { "name" : "Alerting", "level" : "intermediate" }, { "name" : "Failure recovery", "level" : "intermediate" }, { "name" : "Workload balancing", "level" : "intermediate" }, { "name" : "Data artifact management", "level" : "intermediate" }, { "name" : "Data versioning", "level" : "intermediate" }, { "name" : "Data lineage", "level" : "intermediate" }, { "name" : "Reproducibility", "level" : "intermediate" }, { "name" : "Traceability", "level" : "intermediate" }, { "name" : "Data exploration", "level" : "intermediate" }, { "name" : "Data analysis", "level" : "intermediate" }, { "name" : "ML inference", "level" : "intermediate" } ], "majorSkills" : "Data Infrastructure, Distributed Systems, ML Infrastructure, Data Pipelines", "majorSkillsList" : [ "Data Infrastructure", "Distributed Systems", "ML Infrastructure", "Data Pipelines" ], "coreResponsibilities" : "Architect data infrastructure, Build data infrastructure, Scale data infrastructure, Process video clips, Manage video clips, Design storage systems, Optimize storage systems, Build indexing systems, Build retrieval systems, Support dataset querying, Support dataset filtering, Support dataset iteration, Develop observability frameworks, Implement workload balancing, Implement throughput optimization, Manage data artifacts, Manage data versioning, Manage data lineage, Build internal interfaces, Build lightweight tools, Enable data exploration, Enable data querying, Enable data analysis, Support integration of VLMs, Support scalable deployment of VLMs, Generate metadata", "teamCollaboration" : "Collaboration with researchers; Collaboration with engineers", "domainKnowledge" : "Generalist robotics; Foundation world models; Multimodal datasets; Robotics data formats; Real-world sensor data; Vision-language models", "domainList" : [ "generalist-robotics", "foundation-world-models", "multimodal-datasets", "robotics-data-formats", "real-world-sensor-data", "vision-language-models" ], "domainSpecificKnowledge" : [ "Generalist robotics", "Foundation world models", "Multimodal datasets", "Robotics data formats", "Real-world sensor data", "Vision-language models" ], "toolProficiency" : [ "Ray", "Spark", "DVC", "Delta Lake" ], "problemSolvingSkills" : "Performance optimization; Cost-performance tradeoffs", "qualificationsBasic" : "5+ years of experience in data infrastructure, 5+ years of experience in distributed systems, 5+ years of experience in ML infrastructure, Experience building large-scale data pipelines, Experience operating large-scale data pipelines, Deep understanding of distributed systems, Deep understanding of databases, Deep understanding of indexing strategies, Deep understanding of cloud storage architectures, Experience optimizing data throughput, Experience with workload balancing, Experience with cost-performance tradeoffs, Experience with distributed compute frameworks, Skills in observability, Skills in monitoring, Skills in production reliability, Software engineering fundamentals, Ability to own systems end-to-end", "qualificationsPreferred" : "1B+ samples data pipelines experience, Petabyte-scale systems experience, Experience managing large multimodal datasets, Familiarity with ML training workflows, Familiarity with data lifecycle management, Familiarity with vision-language models, Experience running ML inference workloads, Experience with robotics data formats, Experience with real-world sensor data, Experience with data warehouse technologies, Familiarity with data versioning tooling, Familiarity with data lineage tooling", "remoteFriendly" : false, "rawDescription" : "At Rhoda AI, we’re building the next generation of generalist intelligent robots. We own the full robotics stack from high-performance hardware and robot systems to the infrastructure and state-of-the-art foundation world models that control our robots. Our robots are designed to be generalists capable of operating in complex, real-world environments and handling long-tail edge cases, made possible by our cutting edge research and end-to-end system design. We've raised over $400M and are investing aggressively in model research, infrastructure, hardware development, and manufacturing scale-up to make generalist robotics a reality. We're looking for Data Infrastructure MLEs to scale the systems that power our model training data pipeline, from raw ingestion and storage to indexing, retrieval, and throughput optimization at massive scale. We hire across levels — from senior to staff. What You'll Do - Architect, build, and scale a high-throughput data infrastructure that processes and manages billions of video clips with strong guarantees around reliability, latency, and cost efficiency - Design and optimize large-scale storage systems (cloud object storage, databases, metadata stores) for multimodal datasets - Build efficient indexing and retrieval systems to support fast dataset querying, filtering, and iteration for research and production use cases - Develop observability frameworks for data pipelines including monitoring, alerting, failure recovery, and performance optimization - Implement intelligent workload balancing and throughput optimization across distributed compute and storage systems - Manage data artifacts, versioning, and lineage to ensure reproducibility and traceability across training runs - Build internal interfaces and lightweight tools that enable researchers and engineers to explore, query, and analyze large datasets at scale - Support integration and scalable deployment of vision-language models (VLMs) within data pipelines for screening, enrichment, or metadata generation What We're Looking For - 5+ years of experience in data infrastructure, distributed systems, ML infrastructure, or a closely related field - Strong experience building and operating large-scale data pipelines (1B+ samples or petabyte-scale systems preferred) - Deep understanding of distributed systems, databases, indexing strategies, and cloud storage architectures - Experience optimizing data throughput, workload balancing, and cost-performance tradeoffs in cloud environments - Experience with distributed compute frameworks such as Ray or Spark for large-scale data processing and transformation - Strong skills in observability, monitoring, and production reliability for high-scale systems - Strong software engineering fundamentals with the ability to own systems end-to-end, from design to production - Staff-level candidates are expected to define technical direction and own architectural decisions independently; senior candidates execute complex systems work with strong fundamentals and growing scope Nice to Have (But Not Required) - Experience managing large multimodal datasets - Familiarity with ML training workflows and data lifecycle management - Familiarity with vision-language models (VLMs) and experience running ML inference workloads at scale in distributed or cloud environments - Experience with robotics data formats or real-world sensor data (video, proprioception, teleoperation logs) - Experience with data warehouse technologies (e.g., Snowflake, BigQuery, or Redshift) for large-scale data storage, querying, and analytics - Familiarity with data versioning and lineage tooling (e.g., DVC, Delta Lake, or similar) Why This Role - Own the data foundation that everything else runs on — model quality is only as good as the data infrastructure beneath it - Direct collaboration with research and ML systems teams; your work has immediate, measurable impact on training velocity - High ownership in a small team — you'll make real architectural decisions, not execute tickets - Help build the infrastructure that powers robots operating in the real world, at scale", "summaryDescription" : "Research Engineer - Data Infrastructure at Rhoda AI. Skills: Data Infrastructure, Distributed Systems, ML Infrastructure, Data Pipelines. Architect data infrastructure. Build data infrastructure", "createdAt" : "2026-06-14T18:49:57.612", "lastUpdated" : "2026-06-16T06:05:20.878", "ingestTimestamp" : "2026-06-14T18:49:57.612", "mongoId" : "6a2ca17574d8ee00a09a5954", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 185000, "salaryAnnualMax" : 265000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data pipeline optimization", "Storage system optimization", "Indexing systems", "Retrieval systems", "Dataset querying", "Dataset filtering", "Dataset iteration", "Observability frameworks", "Monitoring", "Alerting", "Failure recovery", "Workload balancing", "Data artifact management", "Data versioning", "Data lineage", "Reproducibility", "Traceability", "Data exploration", "Data analysis", "ML inference", "Data Infrastructure", "Distributed Systems", "ML Infrastructure", "Data Pipelines", "System design", "ML infrastructure", "Data infrastructure", "Distributed systems", "Production reliability", "Performance optimization", "Cost efficiency", "Generalist robotics", "Foundation world models", "Multimodal datasets", "Robotics data formats", "Real-world sensor data", "Vision-language models", "Ray", "Spark", "DVC", "Delta Lake" ], "skillCount" : 41, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 744.2481, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2c6c6d74d8ee00a0918b14", "title" : "Cloud & AI Infrastructure Engineer", "company" : "Hanwha Energy USA", "industry" : "Climate Tech", "salary" : { "min" : 160000.0, "max" : 190000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Houston, Texas, United States", "locations" : [ "Houston", "Texas", "United States" ], "timestamp" : "2026-06-15T09:57:32.911", "fingerprint" : "a46389f9d87d79b120ba4331d080263c2eb7c2a2ab122019148af6e531b1be0f", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/hanwhaenergyusa/jobs/4224591009", "externalId" : "4224591009", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Houston", "state" : "Texas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "29.7589382,-95.3676974" } ], "locationText" : "Houston, Texas, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Azure, AI, Terraform, Bicep, ARM templates, CI/CD, Logging, Telemetry, Monitoring, Observability, Identity and access, Networking, Security, Tagging, Azure OpenAI", "professionalSkills" : [ "Platform engineering", "DevOps", "Infrastructure engineering", "Cloud architecture", "Cost optimization", "Chargeback visibility", "Operational standards", "Architecture discussions", "Reliability engineering", "Cross-functional collaboration" ], "hardSkillsList" : [ "Infrastructure provisioning", "Pipeline engineering", "Cloud cost reporting", "Backup and resiliency", "Recovery and alerting", "Support readiness" ], "hardSkills" : [ { "name" : "Infrastructure provisioning", "level" : "intermediate" }, { "name" : "Pipeline engineering", "level" : "intermediate" }, { "name" : "Cloud cost reporting", "level" : "intermediate" }, { "name" : "Backup and resiliency", "level" : "intermediate" }, { "name" : "Recovery and alerting", "level" : "intermediate" }, { "name" : "Support readiness", "level" : "intermediate" } ], "majorSkills" : "Azure infrastructure, AI platform, Infrastructure-as-code, CI/CD pipelines", "majorSkillsList" : [ "Azure infrastructure", "AI platform", "Infrastructure-as-code", "CI/CD pipelines" ], "coreResponsibilities" : "Design and provision Azure and AI resources, Establish and enforce standards, Build and maintain CI/CD pipelines, Implement and support logging, telemetry, monitoring, and observability, Partner with Application Development and Data Management, Manage Azure and AI platform environments, Monitor and optimize Azure and Azure OpenAI usage, Partner with Finance and IT leadership, Support identity, access, secrets, and security practices, Help define and maintain operational standards, Troubleshoot deployment, performance, connectivity, and infrastructure issues, Contribute to architecture discussions, Document cloud patterns, standards, deployment approaches, and support, Evaluate and introduce appropriate tools and patterns", "teamCollaboration" : "Application Development; Data Management; Software developers; Data engineers; Technical leadership; Finance and IT leadership", "domainKnowledge" : "AI agents; Copilots; Automations; Enterprise data workloads; AI-enabled solutions; Hyperscaler solutions; Data center development", "domainList" : [ "ai-agents", "copilots", "automations", "enterprise-data-workloads", "ai-enabled-solutions", "hyperscaler-solutions", "data-center-development" ], "domainSpecificKnowledge" : [ "AI agents", "Copilots", "Automations", "Enterprise data workloads", "AI-enabled solutions", "Hyperscaler solutions", "Data center development" ], "toolProficiency" : [ "Terraform", "Bicep", "ARM templates" ], "documentationSkills" : "Document cloud patterns; Document standards; Document deployment approaches; Document support procedures", "problemSolvingSkills" : "Troubleshooting; Problem-solving", "outcomesObjectives" : "Azure environments are provisioned consistently; AI-enabled applications and agents are deployed; Logging, observability, and alerting are enough; Azure and Azure OpenAI usage is monitored and optimized; Cloud standards are followed consistently; Application Development and Data Management teams can move faster; IT leadership and Finance have clearer visibility", "qualificationsBasic" : "Bachelor's degree in Information Systems, 4+ years of experience in cloud engineering, Hands-on experience with Microsoft Azure services, Experience with infrastructure-as-code, Experience building and maintaining CI/CD pipelines, Experience implementing monitoring, logging, alerting, and observability, Experience supporting production applications and cloud platforms, Troubleshooting and problem-solving skills, Ability to work effectively with software developers", "qualificationsPreferred" : "Experience supporting AI or machine learning workloads in Azure, Familiarity with Azure OpenAI, Experience with containerization, orchestration, or modern hosting models, Experience with FinOps, cloud cost optimization, Experience with secrets management, Familiarity with observability and telemetry practices", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "COMPANY OVERVIEW Hanwha Energy USA, headquartered in Houston, Texas, is part of the Hanwha Group—a FORTUNE Global 300 company and one of South Korea’s most respected business enterprises. With over a decade of experience delivering high-quality, utility-scale energy projects across North America, Hanwha Energy USA has evolved into a comprehensive energy solutions provider. Our portfolio now spans utility-scale renewables, natural gas generation, retail electricity, and strategic partnerships that power America’s growing data center industry. Our expertise covers the entire energy value chain—from project development and engineering to construction, operations, and maintenance. By integrating advanced technologies, proven processes, and strong partnerships, we deliver reliable, customized solutions that meet the dynamic needs of local energy markets. Hanwha Energy USA is actively advancing strategic initiatives in natural gas generation and data center development, including hyperscaler solutions on both sides of the meter. We are proud to serve as the parent company of: Hanwha Renewables – specializing in utility-scale solar and battery energy storage systems (BESS) Chariot Energy – providing retail electricity services for residential, commercial, and industrial customers in deregulated markets POSITION OVERVIEW We are seeking a Cloud & AI Infrastructure Engineer to design, build, operate, and optimize the Azure and AI platform that supports our internal applications, AI agents, copilots, automations, and enterprise data workloads. This role is responsible for providing a secure, reliable, and cost-effective cloud foundation as our AI and application landscape scales. The ideal candidate will bring strong hands-on experience with Azure infrastructure, infrastructure-as-code, CI/CD, monitoring, observability, and cloud cost optimization. This person will work closely with Application Development and Data Management to ensure AI-enabled solutions are production-ready, well-governed, and operationally supportable. This is not a general infrastructure support role. We are looking for an engineer who can help establish modern cloud engineering discipline around provisioning, deployment, logging, monitoring, security, and cost control for AI-enabled systems. The employee may be required to perform other job-related duties as requested by management. All duties will be assigned in accordance with applicable laws and company policies. RESPONSIBILITIES Design and provision Azure and AI resources using infrastructure-as-code, ensuring consistency, scalability, and maintainability. Establish and enforce standards for networking, identity, monitoring, security, tagging, and cloud resource governance. Build and maintain CI/CD pipelines for AI-enabled applications, internal platforms, agents, and automations. Implement and support logging, telemetry, monitoring, and observability practices for AI and cloud-based workloads. Partner with Application Development and Data Management to ensure solutions are deployed and operated in a secure, reliable, and supportable manner. Manage Azure and AI platform environments across development, testing, and production. Monitor and optimize Azure and Azure OpenAI usage and spend, right-size resources, and help improve cloud cost visibility and efficiency. Partner with Finance and IT leadership on cloud cost reporting, chargeback visibility, and optimization opportunities. Support identity, access, secrets, and security practices required for enterprise cloud and AI workloads. Help define and maintain operational standards for backup, resiliency, recovery, alerting, and support readiness. Troubleshoot deployment, performance, connectivity, and infrastructure issues affecting applications, agents, and cloud services. Contribute to architecture discussions related to hosting, integration, scaling, environment design, and operational controls. Document cloud patterns, standards, deployment approaches, and support procedures in a clear and practical way. Evaluate and introduce appropriate tools and patterns that improve reliability, delivery speed, visibility, and cost management. REQUIRED QUALIFICATIONS Bachelor’s degree in Information Systems, Computer Science, Engineering, or a related field. Equivalent experience may be considered. 4+ years of experience in cloud engineering, platform engineering, DevOps, or infrastructure engineering. Strong hands-on experience with Microsoft Azure services and cloud architecture. Experience with infrastructure-as-code such as Terraform, Bicep, ARM templates, or similar tools. Experience building and maintaining CI/CD pipelines for application and platform deployment. Experience implementing monitoring, logging, alerting, and observability for production systems. Understanding of identity, access control, security, and networking concepts in cloud environments. Experience supporting production applications and cloud platforms with a focus on reliability and operational excellence. Strong troubleshooting and problem-solving skills. Ability to work effectively with software developers, data engineers, and technical leadership. Preferred Qualifications Experience supporting AI or machine learning workloads in Azure. Familiarity with Azure OpenAI and the infrastructure patterns needed to support AI-enabled applications. Experience with containerization, orchestration, or modern hosting models. Experience with FinOps, cloud cost optimization, tagging governance, or cost reporting. Experience with secrets management, policy enforcement, and secure deployment patterns. Experience in environments with custom internal applications, integrations, and growing cloud platforms. Familiarity with observability and telemetry practices for distributed systems and AI applications. Key Skills Azure architecture and provisioning Infrastructure-as-code CI/CD pipeline engineering Logging and observability Monitoring and alerting Identity and access controls Cloud networking and security Azure OpenAI platform support Cloud cost optimization Production support and reliability engineering Cross-functional technical collaboration What Success Looks Like In this role, success means: Azure environments are provisioned consistently and governed effectively AI-enabled applications and agents are deployed through repeatable and reliable pipelines Logging, observability, and alerting are strong enough to support production operations Azure and Azure OpenAI usage is monitored and optimized for both performance and cost Cloud standards for identity, networking, security, and tagging are followed consistently Application Development and Data Management teams can move faster because the platform foundation is stable and well run IT leadership and Finance have clearer visibility into cloud consumption and optimization opportunities COMPENSATION: $160,000 - $190,000 salary Attention external recruitment firms, we will not accept any unsolicited resumes at this time. Please do not contact any internal member of our company to discuss the position or to solicit candidates. Hanwha Energy USA provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability or genetics. www.hanwhaenergyusa.com", "summaryDescription" : "Cloud & AI Infrastructure Engineer at Hanwha Energy USA. Skills: Azure infrastructure, AI platform, Infrastructure-as-code, CI/CD pipelines. Design and provision Azure and AI resources. Establish and enforce standards", "postedDate" : "2026-06-14T08:01:15.814", "createdAt" : "2026-06-14T08:01:15.814", "lastUpdated" : "2026-06-15T09:57:32.911", "ingestTimestamp" : "2026-06-14T08:01:15.814", "mongoId" : "6a2c6c6d74d8ee00a0918b14", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 160000, "salaryAnnualMax" : 190000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Infrastructure provisioning", "Pipeline engineering", "Cloud cost reporting", "Backup and resiliency", "Recovery and alerting", "Support readiness", "Azure infrastructure", "AI platform", "Infrastructure-as-code", "CI/CD pipelines", "Platform engineering", "DevOps", "Infrastructure engineering", "Cloud architecture", "Cost optimization", "Chargeback visibility", "Operational standards", "Architecture discussions", "Reliability engineering", "Cross-functional collaboration", "AI agents", "Copilots", "Automations", "Enterprise data workloads", "AI-enabled solutions", "Hyperscaler solutions", "Data center development", "Terraform", "Bicep", "ARM templates" ], "skillCount" : 30, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 737.4648, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Energy", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2d0b4474d8ee00a0accdc0", "title" : "Senior / Staff Software Engineer, Agentic Engineering", "company" : "Abridge", "industry" : "Builder", "salary" : { "min" : 230000.0, "max" : 290000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "SF Office", "locations" : [ "SF Office" ], "timestamp" : "2026-06-15T07:49:52.349", "fingerprint" : "e13297e5bfeac1800f3526c38a589e15b6da1d4b18dc6fc089eef22f8a17386e", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/abridge/5413b10b-532f-46a7-b1f3-d5490d78120e/application", "externalId" : "5413b10b-532f-46a7-b1f3-d5490d78120e", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, CI/CD, DevOps, Cloud, Kubernetes, AWS, GCP, LLM", "professionalSkills" : [ "Systems thinking", "Developer ergonomics", "Feedback loops", "Development velocity" ], "hardSkillsList" : [ "Build tooling", "MCP servers", "AI-assisted development", "Infrastructure tooling", "Operational efficiency" ], "hardSkills" : [ { "name" : "Build tooling", "level" : "intermediate" }, { "name" : "MCP servers", "level" : "intermediate" }, { "name" : "AI-assisted development", "level" : "intermediate" }, { "name" : "Infrastructure tooling", "level" : "intermediate" }, { "name" : "Operational efficiency", "level" : "intermediate" } ], "majorSkills" : "Agentic infrastructure, AI tooling, CI/CD, Developer experience", "majorSkillsList" : [ "Agentic infrastructure", "AI tooling", "CI/CD", "Developer experience" ], "coreResponsibilities" : "Build developer infrastructure, Evolve developer infrastructure, Own CI/CD systems, Build tooling, Build developer platforms, Improve velocity, Improve reliability, Drive improvements, Design agentic workflows, Implement agentic workflows, Build MCP servers, Build autonomous agents, Build AI-assisted tooling, Embed AI into lifecycle, Help teams integrate tools, Own developer experience, Improve developer journey, Eliminate friction, Drive technical excellence, Improve developer ergonomics, Improve feedback loops, Improve development velocity, Evaluate AI tooling, Adopt AI tooling, Guide adoption", "teamCollaboration" : "Across teams; Across functions", "domainKnowledge" : "Healthcare; Generative AI; Clinical documentation; EMR integrations; AI for healthcare", "domainList" : [ "healthcare", "generative-ai", "clinical-documentation", "emr-integrations", "ai-for-healthcare" ], "domainSpecificKnowledge" : [ "Healthcare", "Generative AI", "Clinical documentation", "EMR integrations", "AI for healthcare" ], "toolProficiency" : [ "Bazel", "Buck", "GitHub Actions", "Buildkite", "CircleCI", "ArgoCD", "Istio", "Atmos", "LangGraph", "LangChain" ], "communicationSkills" : "Collaborate across teams", "continuousLearning" : "Ongoing learning opportunities", "specialRequirements" : "Minimum 3 days/week in office", "outcomesObjectives" : "Improve build/test times; Improve deployment frequency; Improve onboarding experience; Deliver productivity gains", "qualificationsBasic" : "Experience building CI/CD systems, Experience with agentic frameworks, Experience improving developer experience, Familiarity with public cloud, Experience with containerized environments, Track record leveraging AI tools", "qualificationsPreferred" : "Built internal developer platform, Experience with multi-agent orchestration, Worked in regulated industries", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT ABRIDGE Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients. Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems. We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. THE ROLE Abridge's platform is scaling fast alongside our expanding customer base and product growth. We're building a new agentic engineering team — one of our top company priorities — reporting directly to our CTO. We're looking for Engineers to help build the agentic infrastructure every engineer at Abridge relies on. You'll work at the intersection of AI tooling, CI/CD and developer experience — building the internal systems and agents that power how we develop and ship software. As an early member of this team, you'll tackle high-impact, high-ambiguity problems spanning CI/CD pipelines, MCP servers, and AI agents. Your work will directly shape how engineers build and deploy across Abridge. This is a rapidly-evolving role that sits at the intersection of AI, developer experience, platform engineering, and healthcare. This is a hybrid role with a minimum of 3 days / week (MWF) in our San Francisco office. Please only apply if you are able to commit to this model and/or willing to relocate to San Francisco. WHAT YOU’LL DO - Build and evolve developer infrastructure: Own CI/CD systems, build tooling, and developer platforms that improve velocity and reliability across engineering. Drive measurable improvements in build/test times, deployment frequency, and onboarding experience. - Design and implement agentic workflows: Build MCP servers, autonomous agents, and AI-assisted tooling that embed AI deeply into the development lifecycle. Help teams integrate these tools effectively into their day-to-day work. - Own the developer experience: Improve the end-to-end developer journey — from local development and testing to deployment and observability. Identify and eliminate friction, treating internal engineers as your customers. - Drive technical excellence: Bring strong systems thinking to architecture and tooling decisions that improve developer ergonomics, feedback loops, and development velocity. - Evaluate and adopt AI tooling: Stay current on AI-powered development tools and guide adoption across the engineering org to deliver measurable productivity gains. WHAT YOU’LL BRING - Strong experience building and evolving CI/CD systems and build tooling (e.g., Bazel, Buck, GitHub Actions, Buildkite, CircleCI). - Hands-on experience with agentic frameworks, MCP servers, LLM tooling, or AI-assisted development workflows. - Experience improving developer experience across local development, CI/CD pipelines, internal tooling, and developer workflows. - Familiarity with production systems in public cloud environments (AWS, GCP, or similar). - Experience with containerized environments, Kubernetes, and modern infrastructure tooling (e.g., ArgoCD, Istio, Atmos). - Strong track record of leveraging AI tools and workflows to materially improve engineering velocity and operational efficiency. - Strong communication skills and ability to collaborate across teams and functions. - Genuine passion for Abridge's mission to improve healthcare in America and across the world. BONUS POINTS IF... - You've built or contributed to an internal developer platform (IDP) at scale. - You have experience with multi-agent orchestration (LangGraph, LangChain, or similar). - You've worked in regulated industries or healthcare environments. WHY WORK AT ABRIDGE? At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month. Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business. Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients. We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life. If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. HOW WE TAKE CARE OF ABRIDGERS: - Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employees - Comprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families. - Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA. - Paid Parental Leave: Generous paid parental leave for all full-time employees. - Family Forming Benefits: Resources and financial support to help you build your family. - 401(k) Matching: Contribution matching to help invest in your future. - Personal Device Allowance: Tax free funds for personal device usage. - Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits. - Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more. - Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals. - Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment. - Compensation and Equity: Competitive compensation and equity grants for full time employees. - ... and much more! EQUAL OPPORTUNITY EMPLOYER Abridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability. We provide reasonable accommodations throughout the interview process. If you need reasonable accommodation in applying, interviewing, completing any assessment or otherwise participating in the employee selection process, please contact us at accommodations@abridge.com STAYING SAFE - PROTECT YOURSELF FROM RECRUITMENT FRAUD We are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com http://abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article https://consumer.ftc.gov/consumer-alerts/2023/05/scammers-are-hijacking-job-ads-heres-how-spot-fakes. Please exercise caution and cease communications if something feels suspicious about your interactions. ", "summaryDescription" : "Senior / Staff Software Engineer, Agentic Engineering at Abridge. Skills: Agentic infrastructure, AI tooling, CI/CD, Developer experience. Build developer infrastructure. 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Our robots generate high-rate video, telemetry, and demonstration data every time they move — and that data is what trains our models. Our software team builds the systems that connect robots to learning. Data infrastructure sits at the center of that loop: what gets captured, how it moves, and how fast it becomes training signal. This work runs on real machines, not benchmarks. About the role As a Staff Software Engineer on data infrastructure at Droyd, you'll own the pipelines that carry data from robot to model. You'll architect ingestion from edge devices, streaming transport, storage, and retrieval — and make fleet data immediately usable for training and evaluation. You'll work in person with a small, senior team across robotics, ML, and hardware. Your work will ship directly to deployed systems. This role is based in San Francisco, CA. We're an in-person company. We build faster that way. In this role, you'll - Architect, build, and maintain highly-available data pipelines for robot video, telemetry, and demonstration data - Own the path from robot to training set: edge ingestion, MoQ/WebTransport streaming, storage, indexing, and retrieval - Work with ML and robotics engineers to make fleet data immediately usable for training and evaluation - Improve throughput, reliability, and cost across the full data path - Build tooling that lets the team find, inspect, and trust the data - Help set technical direction for data and infrastructure as the fleet scales We're looking for someone who - Has 5+ years of software development experience - Has hands-on experience architecting and optimizing large-scale data pipelines - Is proficient in Rust, Go, or Python — Rust is a big plus - Has a strong sense of ownership and can drive complex systems end to end - Communicates clearly and works well with ML, robotics, and hardware engineers - Bonus: experience with streaming video, telemetry-heavy systems, or robotics/edge data About Droyd Droyd builds autonomous robotic systems to automate manual work for enterprises. We design the hardware, write the control stack, collect our own data, and train models that run under real-world constraints. If we do this right, robots stop being demos and start being tools people rely on every day. Join us and help build systems that actually ship.", "summaryDescription" : "Data Infrastructure Engineer at Droyd. Skills: Data infrastructure, Data pipelines, Edge ingestion, Streaming transport. Architect data pipelines. Build data pipelines", "createdAt" : "2026-06-14T09:30:59.644", "lastUpdated" : "2026-06-15T09:32:53.036", "ingestTimestamp" : "2026-06-14T09:30:59.644", "mongoId" : "6a2c681574d8ee00a09023ad", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 150000, "salaryAnnualMax" : 250000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data pipeline optimization", "Large-scale data pipelines", "Data infrastructure", "Data pipelines", "Edge ingestion", "Streaming transport", "System design", "Autonomous robotic systems", "Real-time data capture", "Edge devices", "Robotics data", "ML training data", "Telemetry data", "Demonstration data", "Streaming video", "MoQ", "WebTransport", "Fleet scaling" ], "skillCount" : 18, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Lead", "dataQualityScore" : 0.8888889, "_score" : 716.7174, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c5d3474d8ee00a08db1f8", "title" : "Presales Manager - Inference & Agentic AI", "company" : "Paytm", "industry" : "Inference and Agentic AI", "salary" : { "min" : 2500000.0, "max" : 4000000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Presales Manager in the Technology industry in Noida, India, adjusted for seniority and company size." }, "location" : "Noida, Uttar Pradesh", "locations" : [ "Noida, Uttar Pradesh", "Gurugram, Haryana" ], "timestamp" : "2026-06-16T00:30:56.092", "fingerprint" : "6b852a010cea8da50cd8e4a17b3f9cb108c30e576c309b1b61d31f65d3640633", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/paytm/e20a86ce-bf62-4fac-9d63-24364f69bd43/apply", "externalId" : "e20a86ce-bf62-4fac-9d63-24364f69bd43", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Noida", "state" : "Uttar Pradesh", "country" : "India", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "28.5706333,77.3272147" } ], "locationText" : "Noida, Uttar Pradesh, India", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "experienceMinYears" : 3, "experienceMaxYears" : 6, "experienceLevel" : "Manager", "technicalSkills" : "APIs, Integrations, SaaS platforms, Enterprise applications, CRM platforms, Databases, Cloud technologies, AI, Automation", "professionalSkills" : [ "Solution design", "Technical consulting", "Stakeholder management", "Sales enablement", "Problem-solving" ], "hardSkillsList" : [ "Solution selling", "Technical proposals", "Product demos", "Proof of Concepts" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Solution selling", "level" : "intermediate" }, { "name" : "Technical proposals", "level" : "intermediate" }, { "name" : "Product demos", "level" : "intermediate" }, { "name" : "Proof of Concepts", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Inference AI, Agentic AI, Solutioning, Enterprise Sales", "majorSkillsList" : [ "Inference AI", "Agentic AI", "Solutioning", "Enterprise Sales" ], "coreResponsibilities" : "Partner with Enterprise Sales teams, Understand client requirements, Map solutions to client needs, Conduct discovery sessions, Identify business challenges, Create solution recommendations, Deliver customized product demos, Deliver solution walkthroughs, Deliver Proof of Concepts (POCs), Act as a technical advisor, Address product queries, Address integration queries, Address architecture queries, Address implementation queries, Create solution documents, Create proposal inputs, Create RFP responses, Create technical FAQs, Create sales enablement assets, Collaborate with Product teams, Collaborate with Engineering teams, Collaborate with Onboarding teams, Collaborate with Business teams, Ensure seamless solution delivery, Capture client feedback, Provide insights for product improvement, Provide insights for customer experience improvement, Support enterprise deal closures, Provide solutioning for deals, Manage stakeholders for deals, Provide technical consulting for deals", "teamCollaboration" : "Enterprise Sales teams; Product teams; Engineering teams; Onboarding teams; Business teams", "domainKnowledge" : "Inference AI; Agentic AI; AI automation; Digital Transformation", "domainList" : [ "inference-ai", "agentic-ai", "ai-automation", "digital-transformation" ], "domainSpecificKnowledge" : [ "Inference AI", "Agentic AI", "AI automation", "Digital Transformation" ], "toolProficiency" : [ "Productivity tools", "CRM tools", "Collaboration tools" ], "communicationSkills" : "Presentation skills; Technical communication", "problemSolvingSkills" : "Analytical skills; Problem-solving skills", "qualificationsBasic" : "3–6 years of experience in Pre-Sales, Solution Consulting, Solutions Engineering, Product Consulting, or Enterprise Technology roles, Understanding of APIs, integrations, SaaS platforms, enterprise applications, and solution design, Experience supporting demos, POCs, RFPs, technical workshops, and enterprise sales cycles, Excellent communication and stakeholder management skills, Experience in Pre-Sales, Solution Consulting, or Enterprise Solutioning, Good understanding of APIs, CRM platforms, databases, cloud technologies, and enterprise integrations, Ability to create solution designs, integration workflows, POCs, demos, and technical proposals, Excellent communication and presentation skills, Ability to simplify complex AI, automation, and technology concepts, Analytical and problem-solving skills, Hands-on experience with productivity, CRM, and collaboration tools, Bachelor's degree from a Tier-1 institution", "qualificationsPreferred" : "MBA from a Tier-1 institution", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "## Description Pre-sales Manager, Inference and Agentic AI - Paytm Location: Noida Company: Paytm About Paytm: Paytm is a pioneer of digital payments in India, serving over 450 million consumers and 45 million merchants across payments, financial services, and commerce. Over the years, Paytm has built deep in-house capabilities across technology, data, and operations to operate at scale with high reliability. Paytm is building a full stack AI platform focussed on Inference and Agents, enabling large enterprises to deploy AI driven automation across sales, service, operations, and analytics. The Inference and Agentic AI team operates as a cross functional unit spanning engineering, product, data science, business management, and sales, and owns the full lifecycle of AI solutions from opportunity discovery to deployment and scale. Pre-Sales Manager | Paytm AI Key Responsibilities \uD83D\uDD39 Partner with Enterprise Sales teams to understand client requirements and map them to Paytm AI solutions. \uD83D\uDD39 Conduct discovery sessions, identify business challenges, and create solution recommendations. \uD83D\uDD39 Deliver customized product demos, solution walkthroughs, and Proof of Concepts (POCs) for enterprise clients. \uD83D\uDD39 Act as a technical advisor, addressing product, integration, architecture, and implementation-related queries. \uD83D\uDD39 Create solution documents, proposal inputs, RFP responses, technical FAQs, and sales enablement assets. \uD83D\uDD39 Collaborate with Product, Engineering, Onboarding, and Business teams to ensure seamless solution delivery. \uD83D\uDD39 Capture client feedback and provide insights to improve product capabilities and customer experience. \uD83D\uDD39 Support enterprise deal closures through strong solutioning, stakeholder management, and technical consulting. Ideal Candidate ✔ 3–6 years of experience in Pre-Sales, Solution Consulting, Solutions Engineering, Product Consulting, or Enterprise Technology roles. ✔ Strong understanding of APIs, integrations, SaaS platforms, enterprise applications, and solution design. ✔ Experience supporting demos, POCs, RFPs, technical workshops, and enterprise sales cycles. ✔ Excellent communication and stakeholder management skills. ✔ Passion for AI, Automation, Enterprise Software, and Digital Transformation. Skills & Qualifications ✔ Strong experience in Pre-Sales, Solution Consulting, or Enterprise Solutioning. ✔ Good understanding of APIs, CRM platforms, databases, cloud technologies, and enterprise integrations. ✔ Ability to create solution designs, integration workflows, POCs, demos, and technical proposals. ✔ Excellent communication and presentation skills with the ability to engage both technical and business stakeholders. ✔ Ability to simplify complex AI, automation, and technology concepts for enterprise clients. ✔ Strong analytical and problem-solving skills with a consultative approach. ✔ Hands-on experience with productivity, CRM, and collaboration tools. Educational Qualification \uD83C\uDF93 Must Have: Bachelor's degree from a Tier-1 institution (IITs, SRCC, St. Stephen's, BITS Pilani, NITs, etc.) \uD83C\uDF93 Preferred: MBA from a Tier-1 institution (IIM Ahmedabad, Bangalore, Calcutta, ISB, etc.)", "summaryDescription" : "Presales Manager - Inference & Agentic AI at Paytm. 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0.95 }, { "id" : "6a2c8db174d8ee00a0979a09", "title" : "Senior Infrastructure Engineer (AI-First)", "company" : "MUBI", "industry" : "Engineering", "salary" : { "min" : 85000.0, "max" : 120000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior Infrastructure Engineer in London, UK, with adjustments for the media industry and company size." }, "location" : "London", "locations" : [ "London" ], "timestamp" : "2026-06-15T07:17:20.575", "fingerprint" : "9c6249006bc3ca14f6fbba3ce9f20c7c7b77b5b8039d88b51aae5e5e09d40a11", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/mubi/f6b508c2-2e17-4ffe-862e-07258731eccc/application", "externalId" : "f6b508c2-2e17-4ffe-862e-07258731eccc", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AWS, Kubernetes, EKS, Terraform, Chef, Jenkins, ArgoCD, Helm, Kustomize, ELK Stack, Prometheus, Thanos, Grafana, Datadog, Kafka, Nginx, Lua, MariaDB, PostgreSQL, Claude, MCP, Python, Go, Ruby", "professionalSkills" : [ "System architecture", "Technical leadership", "Agentic patterns", "Incident response", "Automated incident response", "Intelligent observability", "Support ticket triaging", "CI/CD pipelines", "Data pipelines", "Event-driven architectures", "Observability", "SLO commitments", "Availability", "Reliability targets", "Automation" ], "hardSkillsList" : [ "Software development", "Infrastructure engineering", "DevOps", "Cloud infrastructure management", "Kubernetes internals", "Linux debugging", "Networking automation", "Security assessment", "Distributed systems design", "High availability design", "SLO management", 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"name" : "IaC implementation", "level" : "intermediate" }, { "name" : "CI/CD implementation", "level" : "intermediate" }, { "name" : "CDN operation", "level" : "intermediate" }, { "name" : "Cloud infrastructure management", "level" : "intermediate" }, { "name" : "Kubernetes operator development", "level" : "intermediate" }, { "name" : "Data pipeline design", "level" : "intermediate" }, { "name" : "Event-driven architecture design", "level" : "intermediate" }, { "name" : "Observability implementation", "level" : "intermediate" }, { "name" : "LLM API integration", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Mentoring" } ], "majorSkills" : "Infrastructure engineering, Agentic automation, Platform engineering, Kubernetes", "majorSkillsList" : [ "Infrastructure engineering", "Agentic automation", "Platform engineering", "Kubernetes" ], "coreResponsibilities" : "Design agentic workflows, Build agentic workflows, Build MCP servers, Build AI-powered automation, Assess security surface, Own security surface, Build internal tools, Build internal services, Prototype rapidly, Collaborate with product engineers, Write production-quality code, Design EKS clusters, Run EKS clusters, Evolve EKS clusters, Build CI/CD pipelines, Improve CI/CD pipelines, Operate bare-metal CDN, Extend bare-metal CDN, Manage cloud infrastructure, Build Kubernetes operators, Maintain Kubernetes operators, Build Kubernetes controllers, Maintain Kubernetes controllers, Design data pipelines, Operate data pipelines, Design event-driven architectures, Operate event-driven architectures, Maintain observability, Improve observability, Define SLO commitments, Uphold SLO commitments, Automate everything", "teamCollaboration" : "Peer to engineers; Cross-functional teams", "projectManagementSkills" : [ "Agile" ], "domainKnowledge" : "Distributed systems; High availability; SLO-driven operations; Cloud-native architecture; Agentic workflow patterns; AI-powered automation; Bare-metal servers; CDN infrastructure; Event-driven architectures; Video streaming", "domainList" : [ "distributed-systems", "high-availability", "slo-driven-operations", "cloud-native-architecture", "agentic-workflow-patterns", "ai-powered-automation", "bare-metal-servers", "cdn-infrastructure", "event-driven-architectures", "video-streaming" ], "domainSpecificKnowledge" : [ "Distributed systems", "High availability", "SLO-driven operations", "Cloud-native architecture", "Agentic workflow patterns", "AI-powered automation", "Bare-metal servers", "CDN infrastructure", "Event-driven architectures", "Video streaming" ], "toolProficiency" : [ "AWS", "Kubernetes", "EKS", "Terraform", "Chef", "Jenkins", "ArgoCD", "Helm", "Kustomize", "ELK Stack", "Prometheus", "Thanos", "Grafana", "Datadog", "Kafka", "Nginx", "MariaDB", "PostgreSQL", "Claude", "MCP" ], "documentationSkills" : "Technical documentation", "innovationCreativity" : "Prototype development", "problemSolvingSkills" : "Root cause analysis; Troubleshooting; Problem ownership", "specialRequirements" : "Hybrid work, Remote considered", "qualificationsBasic" : "5+ years infrastructure experience, 5+ years platform engineering, 5+ years DevOps experience, Software engineering skills, Kubernetes experience, Deep Linux knowledge, Deep networking knowledge, Security-minded, Deep understanding distributed systems, Deep understanding high availability, Deep understanding SLO-driven operations, Technical leadership, Infrastructure as code experience", "qualificationsPreferred" : "Building Kubernetes operators, Building Kubernetes controllers, Building custom platform abstractions, AWS experience, Cloud provider experience, Bare-metal servers experience, CDN operations experience, Backend development background, Full-stack development background, Ruby experience, Python experience, Go experience, Kafka experience, Event-driven architectures experience, Data pipeline design experience, Data pipeline operations experience, Building with LLM APIs, MCP experience, Agentic frameworks experience, AI-powered operational tooling familiarity, AIOps familiarity, Intelligent alerting familiarity, Automated runbooks familiarity, Video streaming domain knowledge", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "ABOUT MUBI MUBI is a global streaming service, production company and film distributor dedicated to elevating great cinema. To make this possible, we create, curate, acquire and champion visionary films, bringing them to audiences all over the world. We have a team of brilliant, dedicated and passionate people to help bring our mission to life. From London to New York, Istanbul to Paris, and Berlin to Mexico - we work together to realize MUBI’s vision. That’s where you come in! Join our global team and help us make great cinema accessible to everyone, everywhere. ABOUT THE ROLE This isn't a traditional DevOps role, and it's not an ML infrastructure role. You're an infrastructure engineer who builds and ships software — internal tools, services, and agentic automation that solve real infrastructure problems. Think automated incident response, intelligent observability, MCP servers that connect infrastructure systems, and support ticket triaging. You apply agentic patterns to the messy operational world, not train models or manage GPUs. We're looking for someone senior — you architect systems, mentor other engineers, and lead by example. You've built real applications and tools in the infra space before, not just configured existing ones. You don't hesitate to poke around unfamiliar systems, take full ownership of problems, and drive them to completion. Our infrastructure team operates on SRE principles: we build reliable, automated systems and eliminate toil. We also build and maintain the platforms that let the rest of engineering deploy, scale, and monitor their services. You'll own problems end-to-end, from bare-metal CDN servers to Kubernetes clusters to the AI-powered workflows that tie everything together. You use AI tools in your own workflow too — not as a novelty, but as a core part of how you build. Small team, high autonomy, direct impact. Hybrid in London (2-3 days/week). Remote considered for strong candidates outside London. WHERE YOU'LL HAVE IMPACT: Build & Ship — Agentic Infrastructure - Design and build agentic workflows for infrastructure operations — incident response, observability, support ticket triaging - Build and maintain MCP servers and AI-powered automation that connects infrastructure systems - Assess and own the security surface of agentic tools and workflows you build — understand what you're exposing and how to lock it down - Build internal tools and services that make the engineering team faster - Prototype rapidly using AI-assisted development workflows - Collaborate with product engineers — you're a peer, not a support function - Write production-quality code, not just glue scripts Platform & Infrastructure - Design, run, and evolve our EKS clusters — the primary platform for all MUBI services - Build and improve CI/CD pipelines (Jenkins, ArgoCD, Helm) - Operate and extend our in-house bare-metal CDN spanning multiple global locations - Manage cloud infrastructure on AWS using Terraform and Chef - Build and maintain Kubernetes operators and controllers to automate platform workflows - Design and operate data pipelines and event-driven architectures using Kafka - Maintain and improve observability (ELK, Prometheus, Grafana, Datadog) - Define and uphold SLO commitments — own availability and reliability targets - Automate everything worth automating TECH STACK - Cloud: AWS, Kubernetes (currently EKS) - IaC: Terraform, Chef - CI/CD: Jenkins, ArgoCD, Helm, Kustomize - Observability: ELK Stack, Prometheus with Thanos, Grafana, Datadog - Streaming/Messaging: Kafka - Servers: Nginx (with Lua), bare-metal CDN - Databases: MariaDB, PostgreSQL - AI/Agents: Claude, MCP, agentic workflow tooling - Languages: Language-agnostic — strong fundamentals matter more than specific languages WHAT YOU'LL BRING - 5+ years in infrastructure, platform engineering, or DevOps - Interest or experience in building agentic workflows, AI-powered automation, or working with LLM APIs - Strong software engineering skills — you've built and shipped applications and tools in the infrastructure space, not just configured existing systems - Strong Kubernetes experience — you understand the internals, not just kubectl apply - Deep Linux and networking knowledge — you're comfortable running, debugging, and automating bare-metal servers, not just clicking around a cloud console - Security-minded — you think about the attack surface of what you build, especially when integrating AI and agentic tools into infrastructure - Deep understanding of distributed systems, high availability, and SLO-driven operations - Technical leadership — you architect solutions, mentor engineers, and raise the bar for the team - Infrastructure as code experience (Terraform) Nice-to-haves: - Experience building Kubernetes operators, controllers, or custom platform abstractions - AWS or other cloud provider experience - Experience with bare-metal servers or CDN operations - Background in backend or full-stack development - Ruby, Python, or Go experience - Experience with Kafka or event-driven architectures - Data pipeline design and operations - Experience building with LLM APIs, MCP, or agentic frameworks - Familiarity with AI-powered operational tooling (AIOps, intelligent alerting, automated runbooks) - Video streaming domain knowledge Don't meet every requirement? Please apply anyway. We're looking for curious, capable people who want to build great things. If you think you'd thrive here, we'd love to talk. We want to make cinema accessible to everyone. We believe people from different backgrounds bring different ideas that foster innovation and engagement, allowing us to attract great people to develop the best experience for our users. MUBI is committed to being an Equal Opportunity Employer. That means it's our responsibility to ensure that all candidates are not discriminated against in our hiring processes and our employment decisions based on their race, color, religion, nationality or ethnic origin, age, gender identity or expression, sex, marital status, physical or mental disability, socioeconomic background, sexual orientation, family or parental status, or any other applicable characteristic.", "summaryDescription" : "Senior Infrastructure Engineer (AI-First) at MUBI. 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Collaborate with analysts; Collaborate with software teams", "domainKnowledge" : "Distributed systems; Data infrastructure; Machine learning; Business intelligence", "domainList" : [ "distributed-systems", "data-infrastructure", "machine-learning", "business-intelligence" ], "domainSpecificKnowledge" : [ "Distributed systems", "Data infrastructure", "Machine learning", "Business intelligence" ], "toolProficiency" : [ "Airflow", "Dbt", "AWS Glue", "Redshift", "Snowflake", "BigQuery", "Delta Lake", "Iceberg", "Parquet" ], "problemSolvingSkills" : "Performance optimization; Cost optimization", "qualificationsBasic" : "5+ years software development, 5+ years programming, 5+ years design/architecture, 6+ years data engineering/DevOps/infrastructure, Hands-on cloud expertise, Proficiency in GO, SQL, Python", "qualificationsPreferred" : "Experience with real-t", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/ About Us: Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role IVS is building the future of interactive video and we are seeking a Data Infrastructure Engineer to design, build, and maintain the systems that power our data-driven organization. In this role, you will ensure that our data pipelines, storage, and processing systems are reliable, scalable, and optimized for analytics, machine learning, and business intelligence use cases. You will collaborate with data engineers, analysts, and software teams to create infrastructure that enables efficient and secure access to high-quality data. You Will - Design, implement, and maintain scalable data infrastructure in AWS cloud - Build and optimize data pipelines (batch and streaming) to support analytics, reporting, and ML workloads. - Ensure data quality, reliability, and observability through monitoring, logging, and automated alerting. -Work closely with data engineering and analytics teams to understand requirements and deliver high-performance solutions. -Champion best practices for security, compliance, and governance in data infrastructure. - Identify opportunities to optimize performance and cost of data platforms. - Stay current with emerging tools, frameworks, and cloud services in the data infrastructure ecosystem. Perks - Medical, Dental, Vision & Disability Insurance - 401(k) - Amazon Employee Discount Basic Qualifications: - 5+ years of non-internship professional software development experience - 5+ years of programming with at least one software programming language experience - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience as a mentor, tech lead or leading an engineering team - 6+ years of experience in data engineering, DevOps, or infrastructure engineering roles. - Strong hands-on expertise with cloud platforms - Proficiency in data pipeline tools (e.g., Airflow, dbt, AWS Glue, Flink). - Experience with data storage technologies (e.g., Redshift, Snowflake, BigQuery, Delta Lake, Iceberg, Parquet). - Proficiency in GO, SQL, and Python for building and maintaining data systems. - Solid understanding of distributed systems and performance optimization. Preferred Qualifications: - Experience with real-time data streaming and event-driven architectures. - Strong hands-on expertise with AWS cloud - Background in observability and monitoring - Knowledge of data governance, security, and compliance best practices - Prior experience supporting machine learning or advanced analytics environments. Twitch is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Senior Software Engineer - Infrastructure at Twitch Interactive, Inc.. Skills: Data infrastructure, Cloud platforms, Data pipelines. Design scalable data infrastructure. Implement scalable data infrastructure", "postedDate" : "2026-06-13T20:14:31.795", "createdAt" : "2026-06-13T20:14:31.795", "lastUpdated" : "2026-06-15T03:43:09.226", "ingestTimestamp" : "2026-06-13T20:14:31.795", "mongoId" : "68c2e425f8b1b0376634c610", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3077569/apply", "salaryAnnualMin" : 151300, "salaryAnnualMax" : 261500, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data pipeline optimization", "Data quality assurance", "Performance optimization", "Cost optimization", "Mentor", "Tech lead", "Data infrastructure", "Cloud platforms", "Data pipelines", "System design", "Reliability", "Scaling", "Distributed systems", "Machine learning", "Business intelligence", "Airflow", "Dbt", "AWS Glue", "Redshift", "Snowflake", "BigQuery", "Delta Lake", "Iceberg", "Parquet" ], "skillCount" : 24, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 1.0, "_score" : 710.77747, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "68ed10ab70f0b99d58e7ba6d", "title" : "Agentic AI Teacher", "company" : "Amazon.com Services LLC", "industry" : "Database Administration, Machine Learning Data Operatio, Artificial Intelligence", "salary" : { "min" : 40400.0, "max" : 86500.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Boston, Massachusetts, USA", "locations" : [ "Boston, Massachusetts, USA" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-16T05:42:03.741", "fingerprint" : "6773eda641049df65d94171f71b24b9c07718697d99fc61da135d6485bb6f6b9", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3105132/apply", "externalId" : "28d1bcb5-eb2a-4e62-a9f9-318db65d629d", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "Bachelor's", "technicalSkills" : "SQL, Python, R, Spark, AWS, GCP, Azure, SageMaker, Vertex AI, ML Studio, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, Tableau, Power BI, Looker", "professionalSkills" : [ "Data modeling", "Statistical analysis", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis" ], "hardSkillsList" : [ "Data science", "Data engineering", "ML/AI", "BI", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills" ], "hardSkills" : [ { "name" : "Data science", "level" : "intermediate" }, { "name" : "Data engineering", "level" : "intermediate" }, { "name" : "ML/AI", "level" : "intermediate" }, { "name" : "BI", "level" : "intermediate" }, { "name" : "Analytics engineering", "level" : "intermediate" }, { "name" : "Quantitative analysis", "level" : "intermediate" }, { "name" : "Statistical methods", "level" : "intermediate" }, { "name" : "ML frameworks", "level" : "intermediate" }, { "name" : "BI platforms", "level" : "intermediate" }, { "name" : "Cloud data stacks", "level" : "intermediate" }, { "name" : "Modelling skills", "level" : "intermediate" } ], "majorSkills" : "Data science, Machine learning, Data engineering, Business intelligence", "majorSkillsList" : [ "Data science", "Machine learning", "Data engineering", "Business intelligence" ], "coreResponsibilities" : "Develop and deploy machine learning models, Build and maintain data pipelines, Design and implement BI solutions, Perform quantitative analysis, Collaborate with stakeholders", "teamCollaboration" : "Cross-functional teams; Stakeholders", "toolProficiency" : [ "SQL", "Python", "R", "Spark", "AWS", "GCP", "Azure", "SageMaker", "Vertex AI", "ML Studio", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "Tableau", "Power BI", "Looker" ], "qualificationsBasic" : "5+ years of experience in data science, Proficiency in SQL, Experience with Python or R", "qualificationsPreferred" : "PhD preferred, Experience with AWS, GCP, or Azure, Experience with ML frameworks, Experience with BI tools", "remoteFriendly" : false, "workSiteFlexibility" : "onsite", "rawDescription" : "Amazon is investing in generative AI and the responsible development and deployment of Large Language Models (LLMs) across all of our businesses. As part of the Data Team, you will deliver high-quality training data to improve and expand our proprietary LLM capabilities. We seek innovative candidates who can solve complex problems and drive technological advancement in AI. Your work will directly impact how Amazon's customers interact with our AI systems across multiple business lines. Key job responsibilities - Create and annotate high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content - Write grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines - Utilize Python and SQL to automate and optimize data processing workflows - Interpret technical documentation to implement solutions accurately - Dive deep into issues and implement solutions independently - Identify and report tooling bugs and suggest improvements - Make sound judgments and logical decisions when faced with ambiguous or incomplete information About the team Amazon strives to be the world’s most customer-centric company, where customers can research and purchase anything they might want online or offline. We set big goals and are looking for people who can help us reach and exceed them. The AGI organization provides AI capabilities for a variety of Amazon products and searches. We provide secure, flexible, cost effective, and high-quality data development services to our customers, that enables them to build advanced ML models. Basic Qualifications: - Bachelor’s degree in a relevant field or equivalent professional experience - Advanced English-level language proficiency (C1+ or equivalent fluency by Common European Framework of Reference for Languages (CEFR) standards) - Proven experience working with written language data, including experience with annotation, and other forms of data markup - Familiarity with critical concepts such as Python, scripting language, data structures etc Preferred Qualifications: - Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy - Experience managing stakeholder relationships across departments - Advanced-level proficiency in multiple languages (C1+ or equivalent fluency by Common European Framework of Reference for Languages (CEFR) standards) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $40,400/year in our lowest geographic market up to $86,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Agentic AI Teacher at Amazon.com Services LLC. Skills: Data science, Machine learning, Data engineering, Business intelligence. Develop and deploy machine learning models. Build and maintain data pipelines", "postedDate" : "2026-06-14T19:07:43.254", "createdAt" : "2026-06-14T19:07:43.254", "lastUpdated" : "2026-06-16T05:42:03.741", "ingestTimestamp" : "2026-06-14T19:07:43.254", "mongoId" : "68ed10ab70f0b99d58e7ba6d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3105132/apply", "salaryAnnualMin" : 40400, "salaryAnnualMax" : 86500, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data science", "Data engineering", "ML/AI", "BI", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Machine learning", "Business intelligence", "Data modeling", "Statistical analysis", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "SQL", "Python", "R", "Spark", "AWS", "GCP", "Azure", "SageMaker", "Vertex AI", "ML Studio", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "Tableau", "Power BI", "Looker" ], "skillCount" : 39, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 706.71826, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2a8ef374d8ee00a0688156", "title" : "Founding Engineer: Agent Infrastructure", "industry" : "Engineering", "salary" : { "min" : 120000.0, "max" : 160000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Founding Engineer in San Francisco, adjusted for industry and company size." }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-14T22:17:47.941", "fingerprint" : "2790b009137ad65ada19a4387c8ac050815be14211ac923374909bb7322c65f8", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/Clera/9843b97e-dee1-4c09-b5e0-84654085aa48/application", "externalId" : "9843b97e-dee1-4c09-b5e0-84654085aa48", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 1, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "APIs, LLM, Linux", "professionalSkills" : [ "System design", "Technical strategy" ], "hardSkillsList" : [ "Agent infrastructure", "Knowledge graph" ], "hardSkills" : [ { "name" : "Agent infrastructure", "level" : "intermediate" }, { "name" : "Knowledge graph", "level" : "intermediate" } ], "majorSkills" : "Agent infrastructure, LLM workflows", "majorSkillsList" : [ "Agent infrastructure", "LLM workflows" ], "coreResponsibilities" : "Design core infrastructure, Build core infrastructure, Operate core infrastructure, Architect production-grade systems, Maintain production-grade systems, Own projects end-to-end, Ship quickly, Collaborate on technical decisions, Collaborate on roadmap priorities, Collaborate on architectural choices, Contribute across the stack, Contribute across the company", "teamCollaboration" : "Founding leadership", "domainKnowledge" : "People-data platform; Agent platform; LLM-powered workflows; Scraping systems; Knowledge graph architecture; Cloud environments; Linux server environments", "domainList" : [ "people-data-platform", "agent-platform", "llm-powered-workflows", "scraping-systems", "knowledge-graph-architecture", "cloud-environments", "linux-server-environments" ], "domainSpecificKnowledge" : [ "People-data platform", "Agent platform", "LLM-powered workflows", "Scraping systems", "Knowledge graph architecture", "Cloud environments", "Linux server environments" ], "documentationSkills" : "Developer documentation", "innovationCreativity" : "Experimental builds", "problemSolvingSkills" : "First-principles thinking", "qualificationsBasic" : "1+ years of professional experience shipping to production", "workSiteFlexibility" : "Onsite", "rawDescription" : "ABOUT THE ROLE We are looking for a Founding Engineer with 1+ years of professional experience shipping to production to join our early-stage team. We are seeking a high-agency, first-principles thinker who thrives in ambiguity and wants real ownership, ideally someone who aspires to be a founder someday. This person will play a pivotal role in building our core agent infrastructure, shaping our technical strategy, and helping us scale aggressively as we push toward Series A. WHAT YOU'LL DO - Design, build, and operate core infrastructure powering our people-data and agent platform, including APIs, LLM-powered workflows, scraping systems, and large-scale knowledge graph architecture - Architect and maintain production-grade systems capable of handling millions of API requests, with a strong focus on performance, cost efficiency, and reliability across cloud and Linux server environments - Own projects end-to-end, from ambiguous problem definition through deployment and iteration, shipping quickly without sacrificing system integrity - Collaborate directly with founding leadership on technical decisions, roadmap priorities, and foundational architectural choices that will define the company's long-term direction - Contribute broadly across the stack and the company, including developer documentation, technical tutorials, internal tooling, and experimental builds that showcase and stress-test our APIs LOCATION San Francisco, CA, United States", "summaryDescription" : "Founding Engineer: Agent Infrastructure. Skills: Agent infrastructure, LLM workflows. Design core infrastructure. Build core infrastructure", "postedDate" : "2026-06-11T22:46:02.004", "createdAt" : "2026-06-11T22:46:02.004", "lastUpdated" : "2026-06-14T22:17:47.941", "ingestTimestamp" : "2026-06-11T22:46:02.004", "mongoId" : "6a2a8ef374d8ee00a0688156", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 120000, "salaryAnnualMax" : 160000, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Agent infrastructure", "Knowledge graph", "LLM workflows", "System design", "Technical strategy", "People-data platform", "Agent platform", "LLM-powered workflows", "Scraping systems", "Knowledge graph architecture", "Cloud environments", "Linux server environments" ], "skillCount" : 12, "jobCategory" : "engineering", "jobSubcategory" : "engineering", "dataQualityScore" : 0.8888889, "_score" : 705.4585, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true }, { "id" : "693072a370f0b99d58ffb5e2", "title" : "Software Dev Engineer II, Sponsored Products and Brands", "company" : "Amazon.com Services LLC", "industry" : "Software Development, Advertising", "salary" : { "min" : 129300.0, "max" : 223600.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T01:56:20.374", "fingerprint" : "6a17f49b31a862ba24c838b4bcbff5dd8ee1f484edcdcd099ce30d7700370668", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3136158/apply", "externalId" : "1127ff1a-55af-4e45-a014-b09ac4000496", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 2, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Generative AI, Large Language Models, LLM, ML infrastructure, Data processing pipelines, LLMOps", "professionalSkills" : [ "System design", "Architecture", "Reliability", "Scaling" ], "hardSkillsList" : [ "Software development", "System design", "Architecture", "Reliability", "Scaling", "Programming" ], "softSkillsList" : [ "Creative problem-solver", "Tackling complex challenges" ], "hardSkills" : [ { "name" : "Software development", "level" : "intermediate" }, { "name" : "System design", "level" : "intermediate" }, { "name" : "Architecture", "level" : "intermediate" }, { "name" : "Reliability", "level" : "intermediate" }, { "name" : "Scaling", "level" : "intermediate" }, { "name" : "Programming", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Creative problem-solver" }, { "name" : "Tackling complex challenges" } ], "majorSkills" : "Generative AI, Large Language Models, LLMOps, Distributed systems", "majorSkillsList" : [ "Generative AI", "Large Language Models", "LLMOps", "Distributed systems" ], "coreResponsibilities" : "Design conversational ad experiences, Develop conversational ad experiences, Integrate AI-driven solutions, Pioneer new approaches, Shape advertising future, Create scalable systems, Deliver personalized ad experiences, Build large-scale systems, Build low-latency systems, Build ML infrastructure, Build data processing pipelines, Implement LLM models, Contribute to LLMOps, Design customer facing functionality, Build customer facing functionality, Operate customer facing functionality", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Conversational AI; Natural language interactions; Advertising ecosystem; Generative AI; Large Language Models", "domainList" : [ "conversational-ai", "natural-language-interactions", "advertising-ecosystem", "generative-ai", "large-language-models" ], "domainSpecificKnowledge" : [ "Conversational AI", "Natural language interactions", "Advertising ecosystem", "Generative AI", "Large Language Models" ], "innovationCreativity" : "Pioneer new approaches; Innovative solutions", "problemSolvingSkills" : "Creative problem-solver; Tackling complex challenges", "outcomesObjectives" : "Grow incremental sales; Enhance shopping experience; Strengthen marketplace", "qualificationsBasic" : "3+ years software development experience, 2+ years system design experience, Experience programming one language", "qualificationsPreferred" : "3+ years full SDLC experience, Bachelor's degree in computer science, Experience developing Agentic AI solutions, Experience deploying Gen AI applications", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "About Sponsored Products and Brands: The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. We are looking for a software dev engineer for the Conversational Ad Experiences (CAX) team within Sponsored Products and Brands (SPB). SPB helps merchants, retail vendors, and brand owners grow incremental sales of their products on Amazon through native product advertising. The CAX team focuses on sponsored conversational shopping experiences powered by large language models (LLMs). The team is working on multiple 'industry first' projects which are ambiguous and challenging, but they offer the opportunity to have a significant impact on both our shoppers and business. As an engineer on the team, you will drive major product and engineering initiatives, build large-scale, low-latency distributed systems, build ML infrastructure and data processing pipelines. You will partner with our science team to implement LLM models in production, and also contribute to LLMOps. You will be responsible for designing, building, and operating key pieces of customer facing functionality impacting hundreds of millions of Amazon shoppers worldwide. #GenAI Key job responsibilities Key job responsibilities • Design and develop net new conversational ad experiences on the Search page • Collaborate with cross-functional teams to integrate AI-driven solutions across our advertising ecosystem • Pioneer new approaches to conversational AI and natural language interactions in advertising • Shape the future of how businesses connect with customers through advertising • Create scalable systems to deliver explicitly personalized ad experiences What we're looking for: • Passionate about Generative AI, Large Language Models, and their real-world applications • Strong software engineering skills • Creative problem-solver who thrives in ambiguity and loves tackling complex challenges • Track record of delivering innovative solutions that drive business impact • Enthusiasm for staying current with the rapidly evolving AI landscape Basic Qualifications: - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language Preferred Qualifications: - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent - Experience developing and deploying Agentic AI solutions - Experience developing and deploying Gen AI applications Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Software Dev Engineer II, Sponsored Products and Brands at Amazon.com Services LLC. Skills: Generative AI, Large Language Models, LLMOps, Distributed systems. Design conversational ad experiences. Develop conversational ad experiences", "postedDate" : "2026-06-13T01:38:27.077", "createdAt" : "2026-06-13T01:38:27.077", "lastUpdated" : "2026-06-15T01:56:20.374", "ingestTimestamp" : "2026-06-13T01:38:27.077", "mongoId" : "693072a370f0b99d58ffb5e2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3136158/apply", "salaryAnnualMin" : 129300, "salaryAnnualMax" : 223600, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Software development", "System design", "Architecture", "Reliability", "Scaling", "Programming", "Creative problem-solver", "Tackling complex challenges", "Generative AI", "Large Language Models", "LLMOps", "Distributed systems", "Conversational AI", "Natural language interactions", "Advertising ecosystem" ], "skillCount" : 15, "jobCategory" : "engineering", "dataQualityScore" : 1.0, "_score" : 699.1083, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Advertising" }, { "id" : "6a2a709974d8ee00a064716a", "title" : "Founding Engineer: Agent Infrastructure", "industry" : "Engineering", "salary" : { "min" : 120000.0, "max" : 160000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Junior Founding Engineer in San Francisco, adjusted for industry and company size." }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-14T20:03:12.245", "fingerprint" : "5a0e51b41a2464cf102fd252dc84f3df9818e925726c3112a4bed609a729df5d", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/clera/9843b97e-dee1-4c09-b5e0-84654085aa48/application", "externalId" : "9843b97e-dee1-4c09-b5e0-84654085aa48", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 1, "experienceMaxYears" : 2, "experienceLevel" : "Entry", "technicalSkills" : "APIs, LLM, Linux", "professionalSkills" : [ "Technical strategy", "System design", "Architecture choices" ], "hardSkillsList" : [ "Knowledge graph architecture", "Scraping systems" ], "hardSkills" : [ { "name" : "Knowledge graph architecture", "level" : "intermediate" }, { "name" : "Scraping systems", "level" : "intermediate" } ], "majorSkills" : "Agent infrastructure, Cloud, Reliability", "majorSkillsList" : [ "Agent infrastructure", "Cloud", "Reliability" ], "coreResponsibilities" : "Design core infrastructure, Build core infrastructure, Operate core infrastructure, Architect production-grade systems, Maintain production-grade systems, Own projects end-to-end, Ship quickly, Collaborate on technical decisions, Collaborate on roadmap priorities, Collaborate on architectural choices, Contribute across the stack, Contribute across the company", "teamCollaboration" : "Founding leadership", "projectManagementSkills" : [ "Roadmap priorities" ], "domainKnowledge" : "People-data platform; Agent platform; Knowledge graph architecture; Cloud environments; Linux server environments", "domainList" : [ "people-data-platform", "agent-platform", "knowledge-graph-architecture", "cloud-environments", "linux-server-environments" ], "domainSpecificKnowledge" : [ "People-data platform", "Agent platform", "Knowledge graph architecture", "Cloud environments", "Linux server environments" ], "documentationSkills" : "Developer documentation", "innovationCreativity" : "Experimental builds", "problemSolvingSkills" : "First-principles thinker; Ambiguity", "outcomesObjectives" : "Scale aggressively", "qualificationsBasic" : "1+ years of professional experience shipping to production", "workSiteFlexibility" : "Onsite", "rawDescription" : "ABOUT THE ROLE We are looking for a Founding Engineer with 1+ years of professional experience shipping to production to join our early-stage team. We are seeking a high-agency, first-principles thinker who thrives in ambiguity and wants real ownership, ideally someone who aspires to be a founder someday. This person will play a pivotal role in building our core agent infrastructure, shaping our technical strategy, and helping us scale aggressively as we push toward Series A. WHAT YOU'LL DO - Design, build, and operate core infrastructure powering our people-data and agent platform, including APIs, LLM-powered workflows, scraping systems, and large-scale knowledge graph architecture - Architect and maintain production-grade systems capable of handling millions of API requests, with a strong focus on performance, cost efficiency, and reliability across cloud and Linux server environments - Own projects end-to-end, from ambiguous problem definition through deployment and iteration, shipping quickly without sacrificing system integrity - Collaborate directly with founding leadership on technical decisions, roadmap priorities, and foundational architectural choices that will define the company's long-term direction - Contribute broadly across the stack and the company, including developer documentation, technical tutorials, internal tooling, and experimental builds that showcase and stress-test our APIs LOCATION San Francisco, CA, United States", "summaryDescription" : "Founding Engineer: Agent Infrastructure. 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Work with other PMs; Work with designers; Work with GTM team; Connect engineering to business; Engage with Sales; Engage with CS", "projectManagementSkills" : [ "Roadmap planning", "Lightweight specs" ], "domainKnowledge" : "Enterprise data; Pharma analytics; CPG RevOps; Finance analytics; Semantic layers; Data governance; Metric definitions; Agentic systems; AI reasoning; AI uncertainty; AI trust; AI workflows; Agent memory; Reasoning chains; Action workflows; AI governance; Vertical intelligence; Conversational analytics; AI-generated interfaces; Onboarding automation; Cross-platform intelligence", "domainList" : [ "enterprise-data", "pharma-analytics", "cpg-revops", "finance-analytics", "semantic-layers", "data-governance", "metric-definitions", "agentic-systems", "ai-reasoning", "ai-uncertainty", "ai-trust", "ai-workflows", "agent-memory", "reasoning-chains", "action-workflows", "ai-governance", "vertical-intelligence", "conversational-analytics", "ai-generated-interfaces", "onboarding-automation", "cross-platform-intelligence" ], "domainSpecificKnowledge" : [ "Enterprise data", "Pharma analytics", "CPG RevOps", "Finance analytics", "Semantic layers", "Data governance", "Metric definitions", "Agentic systems", "AI reasoning", "AI uncertainty", "AI trust", "AI workflows", "Agent memory", "Reasoning chains", "Action workflows", "AI governance", "Vertical intelligence", "Conversational analytics", "AI-generated interfaces", "Onboarding automation", "Cross-platform intelligence" ], "toolProficiency" : [ "AI tools" ], "communicationSkills" : "Executive presentations; Technical documentation", "documentationSkills" : "Spec drafting", "continuousLearning" : "Learning budget; Courses; Conferences; Tools", "innovationCreativity" : "Prototype development", "problemSolvingSkills" : "Root cause analysis; Troubleshooting; Data-driven decision making; Analytical skills", "outcomesObjectives" : "Influence enterprise decisions; Reduce time-to-insight", "qualificationsBasic" : "5+ years product management experience, Shipped AI/ML core products, Experience with AI evaluation frameworks, Enterprise analytics domain knowledge, Agentic systems thinking, Technical background or ability to work with engineering", "qualificationsPreferred" : "Majority in growth-focused roles, Worked in regulated industries, Experience with analytics, BI, data platforms, Experience with AI/ML, Experience designing for AI transparency, Prototype and use AI tools fluently", "remoteFriendly" : false, "rawDescription" : "Tellius enables organizations to get faster insights and act upon cloud-scale enterprise data using AI-powered automation. Any user can ask any question across billions of records via a ChatGPT-like interface, understand “why” metrics change via AI insights that surface hidden key drivers and trends, and leverage agentic flows to perform complex multipart analysis easily — in a self-service manner. Unlike traditional BI tools, Tellius excels at ad hoc analysis, deep dives, and business-friendly advanced analytics. The Role We're looking for an AI-Native Product Manager to own one or more of our core agentic analytics product areas. This is not a traditional PM role where you write specs and hand them off. This is a role where you'll be deeply in the product, using AI tools daily, making autonomous calls, and shipping continuously. You'll own the full lifecycle — from understanding why a pharma brand manager can't trust an AI insight, to defining the product, to shipping it, to measuring whether it actually changed a decision. What You'll Own You'll work across one or more of Tellius's core product pillars: Conversational Analytics — Natural language interaction with enterprise data. Users ask questions; AI agents investigate autonomously and deliver insights with reasoning and evidence. Handles both structured data warehouses and unstructured documents. AI-Generated Interfaces — Moving beyond static dashboards to dynamic, context-aware visualizations. The system generates the right interface for each specific insight — whether that's summary cards, interactive charts, or narrative explanations. Onboarding & Setup Automation — Reducing time-to-first-insight from days to minutes. AI-powered workflows that understand data relationships, suggest transformations, and validate configurations before users go live. Cross-Platform Intelligence — Bringing Tellius's AI capabilities into the tools users already work in. Ambient assistance that understands context across different enterprise applications. Vertical Intelligence — Pre-configured domain knowledge for specific industries (pharma, CPG, finance) — understanding their metrics, workflows, and decision-making frameworks out of the box. You won't own all of these simultaneously. You'll own the ones that match your experience and where you can drive the most impact. But you'll need to understand how they all connect — because Tellius is a platform, and the product decisions in one area affect all the others. What \"AI-Native\" Means Here This isn't a role where \"AI\" is a buzzword in the job title. We mean it operationally: You will use AI tools to do your job. Prototyping, research synthesis, competitive analysis, spec drafting, data exploration — all of it. If you're not reaching for an AI tool first, you're working the wrong way here. You will build AI products. The products you ship involve autonomous agents making decisions, surfacing insights, and taking actions. You need to understand — at a working level — how LLMs reason, where they fail, how to design for uncertainty, and how to build trust into AI-driven workflows. You will think in systems. Agentic analytics isn't a single feature. It's a web of interconnected capabilities: memory, semantic layers, reasoning chains, action workflows, and governance. Your job is to make these systems work together coherently for real enterprise users. What We're Looking For Must-Haves Deep AI Product Experience: You've shipped products where AI/ML is the core interaction, not a bolt-on. You understand the difference between \"AI-powered\" and \"AI-native.\" You've wrestled with hallucination, confidence calibration, and explainability in production — not just in theory. AI Evaluation & Testing Expertise: You've built evaluation frameworks to test and validate agent behavior at scale. You understand how to use LLM-as-a-judge for automated testing, create human evaluation rubrics, design test scenarios that catch edge cases, and measure output quality beyond simple accuracy metrics. You know the difference between vibes-based testing and rigorous validation. Enterprise Analytics Domain Knowledge: You know what a pharma commercial analytics director actually does on a Tuesday. You understand semantic layers, data governance, metric definitions, and why an enterprise user needs to audit an AI's reasoning before acting on it. You don't need to write SQL, but you need to understand why the query matters. Agentic Systems Thinking: You can design product experiences where AI agents work autonomously — and where humans need to understand, guide, and override that autonomy. You think about agent memory, multi-step workflows, proactive vs. reactive triggers, and how to show reasoning without overwhelming users. Speed and Autonomy Tellius is a 75-person company moving fast. You'll make calls without perfect information. You'll ship before it's polished. You'll iterate based on real user feedback, not months of research. You need to be comfortable with this pace and thrive in it. Cross-Functional Collaboration You'll work closely with 44 engineers, 3 other PMs, designers, and a small GTM team. You need to be the person who connects engineering capability to business needs. Sales and CS are your frontline intelligence — you should be in their world regularly, not just at QBRs. Strong Signals 5+ years of product management experience, with a majority in growth-focused roles You've built products in analytics, BI, data platforms, or AI/ML You've worked in a company serving regulated industries (pharma, finance, healthcare) You understand and can articulate the difference between a dashboard product and an agentic product You've designed for AI transparency and explainability You can prototype and use AI tools fluently in your workflow Technical background or ability to work effectively with engineering teams You ask, \"What decision does this enable?\" before \"What feature should we build?\" What We Don't Need A PM who treats AI as a feature checkbox Someone who needs 6 months of onboarding before shipping anything A process-heavy PM who needs a fully defined roadmap before starting work Someone who can't navigate ambiguity — our product surface is expanding rapidly What You'll Do (Day-to-Day) Understand the user deeply. Talk to pharma commercial managers, CPG RevOps teams, and finance analysts. Understand their workflows, their trust requirements, and their relationship with data. Don't rely on secondhand intel — be in the room (or on the call). Define and ship product. Write lightweight specs (not 20-page PRDs). Work with engineers to understand technical constraints and possibilities. Make trade-off calls. Ship. Measure. Iterate. Use AI to move faster—prototype with AI tools. Synthesize research with AI. Draft specs with AI. Explore data with AI. If you're doing something manually that AI could do, stop and fix that first. Think about the platform. Every feature you build connects to the broader Tellius platform. A decision about how Kaiya surfaces insights affects how Apps renders them, which affects how the Browser Extension presents them. Think in systems. Drive outcomes, not features. Your success metric isn't \"shipped 12 features this quarter.\" It's \"influenced 50 enterprise decisions\" or \"reduced time-to-insight from 20 hours to 30 minutes.\" We measure value by what changes in the real world, not what ships in the product. Own trust and governance. Enterprise users — especially those in the pharmaceutical and financial industries — need to trust AI outputs. You'll think about explainability, audit trails, data lineage, and confidence communication as core product requirements, not afterthoughts. Culture: We're an AI-first, outcome-focused, and lean organization. We don't do unnecessary meetings. We do write things down. We move fast and iterate. We trust each other to make calls. And we care deeply about building products that enterprise users actually trust. Compensation & Benefits Competitive base salary + equity (Series stage, early growth) Full benefits package Learning budget for courses, conferences, and tools Ready to Apply? We don't want a cover letter. We want to see how you think. Send us: A product you've shipped that involved AI as a core interaction — what was the hardest trust or explainability problem you solved? OR If you had 30 days at Tellius, what's the first thing you'd investigate and why? That's it. Keep it short. We'll know if you're the right fit.", "summaryDescription" : "Product Manager — Agentic Analytics at Tellius. Skills: AI-Native Product Management, Agentic Analytics, Enterprise Analytics. Own agentic analytics product areas. 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Product; Design; Data Science; Sales; Enterprise customers", "domainKnowledge" : "Agentic AI; Enterprise SaaS; Membership systems; RBAC/permissions; Organization management; Subscriptions; Billing systems; Usage-based pricing; Security; Compliance; Governance", "domainList" : [ "agentic-ai", "enterprise-saas", "membership-systems", "rbac-permissions", "organization-management", "subscriptions", "billing-systems", "usage-based-pricing", "security", "compliance", "governance" ], "domainSpecificKnowledge" : [ "Agentic AI", "Enterprise SaaS", "Membership systems", "RBAC/permissions", "Organization management", "Subscriptions", "Billing systems", "Usage-based pricing", "Security", "Compliance", "Governance" ], "problemSolvingSkills" : "Execution; Break down needs; Ship durable systems; Clear customer impact; Product intuition; Make workflows simple; Make workflows intuitive; Identify problems; Propose solutions; Drive improvements", "qualificationsBasic" : "4+ years software engineering, Backend/Full Stack engineering skills, Building scalable distributed systems, Building product features, Building platform features, Building admin workflows, Building billing workflows, Building permissions workflows", "qualificationsPreferred" : "Experience building enterprise SaaS products, Experience building admin consoles, Experience building membership systems, Experience building RBAC/permissions, Experience building organization management features, Experience with subscriptions, Experience with billing systems, Experience with usage-based pricing, Familiarity with security concerns, Familiarity with compliance concerns, Familiarity with governance concerns, Experience partnering with Sales, Experience partnering with Finance, Experience partnering with Support, Experience partnering with enterprise customers, Time at fast-growing startup, Time on high-ownership engineering team", "remoteFriendly" : true, "rawDescription" : "In 2026, we launched Computer, the defining product for the new era of agentic AI. Millions of people now use Perplexity to transform knowledge into action, and the Enterprise Platform team builds the foundation that lets organizations bring that power to every employee with confidence, control, and scale. Enterprise Platform is the team that brings Perplexity into the workplace. You’ll build user-facing products that help organizations adopt products like Computer in practical, everyday tasks, and also guide organization admins to onboard and enable their teams to use Perplexity products effectively. Tech Stack: Python | Go | PostgreSQL | DynamoDB | AWS | TypeScript | React WHY PERPLEXITY IS DIFFERENT - Craftsmanship. We build high quality, tasteful products targeting both the AI native and AI curious. - Ownership. You identify the problem, design the solution and ship it. - Entrepreneurship. We think like founders, act with urgency, and hustle to deliver for each other and our users. - Scholarship. Work among highly talented peers, pursuing knowledge and truth, upleveling ourselves, our teams, and our products. - Partnership. We amplify each others' strengths, break down silos, and give selflessly to help our colleagues deliver excellence. WHAT YOU'LL DO - Build intelligent products across onboarding, membership management, organization insights, permissions, subscriptions, billing, and usage controls. - Build systems that help organizations manage Perplexity at scale, from first setup through expansion, making it easier for admins to onboard teams, configure features, manage usage, and understand spend. - Collaborate closely with PM, Design, Data Science, Sales, and Enterprise customers to turn complex administrative, billing, and governance needs into simple, reliable product experiences. - Own critical platform primitives end-to-end, from frontend admin flows to backend services, data models, billing integrations, observability, and production operations. QUALIFICATIONS - 4+ years of professional software engineering experience; we’re open to strong junior and mid-level candidates with a track record of shipping. - Backend / Full Stack engineering skills, with experience in designing and building scalable and reliable distributed systems, serving high traffic and a large user base. - Strong execution: you can take ambiguous product needs, break them down, and ship durable systems with clear customer impact. - Experience building product or platform features that require careful data modeling, state management, backend correctness, and high-quality user experience. - Strong product judgment; you can make complex admin, billing, and permissions workflows feel simple and intuitive. - Self-motivated with strong ownership instincts; you identify problems, propose solutions, and drive improvements without waiting for perfect specs. - Genuine interest in AI products and willingness to learn quickly. NICE TO HAVE - Experience building enterprise SaaS products, admin consoles, membership systems, RBAC/permissions, or organization management features. - Experience with subscriptions, billing systems, or usage-based pricing. - Familiarity with security, compliance, or governance concerns in enterprise products. - Experience partnering directly with Sales, Finance, Support, or enterprise customers to solve high-impact product and platform problems. - Time spent at a fast-growing startup or on a high-ownership engineering team.", "summaryDescription" : "Member of Technical Staff (Software Engineer, Enterprise Platform) at Perplexity. Skills: Enterprise Platform, Agentic AI, AI Products. Build intelligent products. 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Stakeholders", "domainKnowledge" : "Cloud data services; ML frameworks; BI platforms; Cloud data stacks", "domainList" : [ "cloud-data-services", "ml-frameworks", "bi-platforms", "cloud-data-stacks" ], "domainSpecificKnowledge" : [ "Cloud data services", "ML frameworks", "BI platforms", "Cloud data stacks" ], "toolProficiency" : [ "Tableau", "Power BI", "Snowflake", "BigQuery", "Redshift", "Databricks", "Dbt", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure" ], "qualificationsBasic" : "5+ years of experience in data science, Proficiency in SQL, Experience with Python or R, Experience with data visualization tools, Experience with cloud platforms", "qualificationsPreferred" : "Master's degree or PhD, Experience with machine learning frameworks, Experience with large-scale data processing systems, Experience with AWS, GCP, or Azure", "remoteFriendly" : false, "workSiteFlexibility" : "onsite", "rawDescription" : "Amazon is investing in generative AI and the responsible development and deployment of Large Language Models (LLMs) across all of our businesses. As part of the Data Team, you will deliver high-quality training data to improve and expand our proprietary LLM capabilities. We seek innovative candidates who can solve complex problems and drive technological advancement in AI. Your work will directly impact how Amazon's customers interact with our AI systems across multiple business lines. Key job responsibilities - Create and annotate high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content - Write grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines - Utilize Python and SQL to automate and optimize data processing workflows - Interpret technical documentation to implement solutions accurately - Dive deep into issues and implement solutions independently - Identify and report tooling bugs and suggest improvements - Make sound judgments and logical decisions when faced with ambiguous or incomplete information About the team Amazon strives to be the world’s most customer-centric company, where customers can research and purchase anything they might want online or offline. We set big goals and are looking for people who can help us reach and exceed them. The AGI organization provides AI capabilities for a variety of Amazon products and searches. We provide secure, flexible, cost effective, and high-quality data development services to our customers, that enables them to build advanced ML models. Basic Qualifications: - Bachelor’s degree in a relevant field or equivalent professional experience - Advanced English-level language proficiency (C1+ or equivalent fluency by Common European Framework of Reference for Languages (CEFR) standards) - Proven experience working with written language data, including experience with annotation, and other forms of data markup - Familiarity with critical concepts such as Python, scripting language, data structures etc Preferred Qualifications: - Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy - Experience managing stakeholder relationships across departments - Advanced-level proficiency in multiple languages (C1+ or equivalent fluency by Common European Framework of Reference for Languages (CEFR) standards) Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $40,400/year in our lowest geographic market up to $86,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Agentic AI Teacher at Amazon.com Services LLC. Skills: Data science, Machine learning, Business intelligence, Data engineering. Develop and deploy machine learning models. Build and maintain data pipelines", "postedDate" : "2026-06-13T19:14:38.999", "createdAt" : "2026-06-13T19:14:38.999", "lastUpdated" : "2026-06-15T06:13:37.124", "ingestTimestamp" : "2026-06-13T19:14:38.999", "mongoId" : "68e6b1d970f0b99d58d66afb", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3103216/apply", "salaryAnnualMin" : 40400, "salaryAnnualMax" : 86500, "salaryBand" : "30k-50k", "hasSalary" : true, "allSkills" : [ "Data science", "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Data modeling", "Statistical analysis", "Cloud data services", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Snowflake", "BigQuery", "Redshift", "Databricks", "Dbt", "Fivetran", "Airflow", "Dbt Cloud", "Delta Lake", "Scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow", "AWS", "GCP", "Azure" ], "skillCount" : 39, "jobCategory" : "engineering", "jobSubcategory" : "data", "seniorityLevel" : "Mid", "dataQualityScore" : 0.8888889, "_score" : 686.5028, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "693c2b8770f0b99d5843fb3f", "title" : "Agentic AI Teacher", "company" : "Evi Technologies Limited", "industry" : "Database Administration, Machine Learning Data Operatio, Artificial Intelligence", "salary" : { "min" : 65000.0, "max" : 95000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Agentic AI Teacher in London, United Kingdom, adjusted for the technology industry." }, "location" : "London, England, GBR", "locations" : [ "London, England, GBR" ], "certifications" : [ "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified" ], "timestamp" : "2026-06-15T03:40:18.291", "fingerprint" : "6e2c3d136dc3e09bb7e1f469e77503892976f83a7ddc7a26c89827570bba6bfc", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3137325/apply", "externalId" : "5648f875-a747-4548-a930-147109c64061", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "onsite", "geo" : "51.5074456,-0.1277653" } ], "locationText" : "London, United Kingdom", "employmentType" : "FULL_TIME", "technicalSkills" : "SQL, Python, R, Scala, Spark, Dbt, Snowflake, BigQuery, Redshift, Databricks, Fivetran, Airflow, Dbt Cloud, Delta Lake, Scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, AWS, S3, Glue, SageMaker, Athena, GCP, Vertex AI, Azure, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "Machine learning", "Business 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Data engineering, Machine learning, Business intelligence", "majorSkillsList" : [ "Data science", "Data engineering", "Machine learning", "Business intelligence" ], "coreResponsibilities" : "Develop and deploy machine learning models, Build and maintain data pipelines, Design and implement data warehousing solutions, Create and manage BI dashboards and reports, Perform data analysis and generate insights, Collaborate with cross-functional teams, Stay updated on emerging technologies", "teamCollaboration" : "Cross-functional teams", "toolProficiency" : [ "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "qualificationsBasic" : "5+ years experience, Bachelor's degree, SQL proficiency", "qualificationsPreferred" : "PhD preferred, GCP Professional Data Engineer certification, AWS Data Analytics certification, Databricks Certified, Dbt Certified", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "Amazon is investing in generative AI and the responsible development and deployment of Large Language Models (LLMs) across all of our businesses. As part of the Data Team, you will deliver high-quality training data to improve and expand our proprietary LLM capabilities. We seek innovative candidates who can solve complex problems and drive technological advancement in AI. Your work will directly impact how Amazon's customers interact with our AI systems across multiple business lines. Key job responsibilities - Create and annotate high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content - Write grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines - Utilize Python and SQL to automate and optimize data processing workflows - Interpret technical documentation to implement solutions accurately - Dive deep into issues and implement solutions independently - Identify and report tooling bugs and suggest improvements - Make sound judgments and logical decisions when faced with ambiguous or incomplete information About the team Amazon strives to be the world’s most customer-centric company, where customers can research and purchase anything they might want online or offline. We set big goals and are looking for people who can help us reach and exceed them. The AGI organization provides AI capabilities for a variety of Amazon products and searches. We provide secure, flexible, cost effective, and high-quality data development services to our customers, that enables them to build advanced ML models. Basic Qualifications: - Advanced-level proficiency in English language (C1+ or equivalent fluency by Common European Framework of Reference for Languages (CEFR) standards). - Proven experience working with written language data, including experience with annotation, and other forms of data markup. Preferred Qualifications: - Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy. - Experience managing stakeholder relationships across departments. - Advanced-level proficiency in multiple languages (C1+ or equivalent fluency by Common European Framework of Reference for Languages (CEFR) standards). - Familiarity with critical concepts such as Python, scripting language, data structures etc. Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "Agentic AI Teacher at Evi Technologies Limited. Skills: Data science, Data engineering, Machine learning, Business intelligence. Develop and deploy machine learning models. Build and maintain data pipelines", "postedDate" : "2026-06-13T17:57:34.972", "createdAt" : "2026-06-13T17:57:34.972", "lastUpdated" : "2026-06-15T03:40:18.291", "ingestTimestamp" : "2026-06-13T17:57:34.972", "mongoId" : "693c2b8770f0b99d5843fb3f", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3137325/apply", "salaryBand" : "50k-75k", "hasSalary" : false, "allSkills" : [ "Statistical methods", "ML frameworks", "BI platforms", "Cloud data stacks", "Modelling skills", "Regression", "Classification", "Clustering", "Time-series analysis", "A/B testing", "Causal inference", "Data science", "Data engineering", "Machine learning", "Business intelligence", "Analytics engineering", "Quantitative analysis", "Statistical modeling", "GCP Professional Data Engineer", "AWS Data Analytics", "Databricks Certified", "Dbt Certified", "Tableau", "Power BI", "Looker", "Metabase", "Superset", "Qlik", "MicroStrategy" ], "skillCount" : 29, 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"Prompt tooling", "Prompt versioning", "Prompt testing", "API integration", "Data pipeline development", "Model evaluation", "Observability tooling", "Monitoring tooling", "Software engineering fundamentals", "Context window", "Agentic workflow", "Crypto ecosystem", "Digital assets", "Regulated domain", "Trustworthiness", "Explainability", "Auditability", "ML lifecycle tooling" ], "softSkillsList" : [ "Curiosity", "Learning velocity", "Holistic thinking", "Direct communication" ], "hardSkills" : [ { "name" : "Model serving infrastructure", "level" : "intermediate" }, { "name" : "Prompt pipelines", "level" : "intermediate" }, { "name" : "Evaluation harnesses", "level" : "intermediate" }, { "name" : "Integration patterns", "level" : "intermediate" }, { "name" : "Agentic workflows", "level" : "intermediate" }, { "name" : "Orchestration scaffolding", "level" : "intermediate" }, { "name" : "Reliability mechanisms", "level" : "intermediate" }, { "name" : "AI observability", "level" : 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"communicationSkills" : "Direct communication", "documentationSkills" : "Documentation", "continuousLearning" : "Learning velocity; Learning orientation; Learning & Development budget", "problemSolvingSkills" : "Reasoning about dependencies; Reasoning about failure modes", "specialRequirements" : "Work from anywhere 90 days", "qualificationsBasic" : "Hands-on experience building with LLMs, Familiarity with AI protocols, Solid software engineering fundamentals, Deep understanding of context window, Exposure to API integration, Exposure to data pipeline development, Exposure to model evaluation, Exposure to testing, Exposure to observability tooling, Exposure to monitoring tooling", "qualificationsPreferred" : "Hands-on experience with LangChain, Hands-on experience with LangSmith, Hands-on experience with Databricks AgentBricks, Experience with prompt engineering, Experience with evaluation dataset design, Experience with LLM output quality assessment, Interest in crypto ecosystem, Experience in regulated domain, Familiarity with MLflow, Familiarity with Databricks ML", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "The impact you will have: This is an opportunity to join Elliptic's AI Platform team at its inception to help build the foundational infrastructure that will power how Elliptic's products think, reason, and act. You will be one of the first engineers working on a centralised AI platform whose purpose is to make AI development faster, safer, and more coherent across the business. That means building the plumbing: the pipelines, the tooling, the evaluation harnesses, the observability layers, and the integration patterns that domain teams will rely on to ship with confidence. You don't need to have done all of this before. What matters is that you are genuinely energised by AI, that you think carefully about how systems fit together, and that you take real pride in building things that others can build on top of. This is a role where curiosity and learning velocity matter as much as prior experience, and where the work you do in the first year will have a lasting shape on how AI, both internally and customer-facing, is engineered at Elliptic. What you will do: - Build and maintain core components of Elliptic's AI platform: model serving infrastructure, prompt pipelines, evaluation harnesses, and integration patterns that allow domain teams to use AI reliably and at scale - Support the development of agentic workflows, including tooling, orchestration scaffolding, and reliability mechanisms, as Elliptic moves toward more autonomous AI capabilities in its products - Instrument AI systems for observability: tracing model calls, tracking token costs, surfacing latency and quality signals, and contributing to the dashboards and alerting that keep production AI systems healthy - Contribute to the tooling and frameworks that govern how prompts are written, versioned, and tested across the organisation, helping to raise the baseline quality of AI interactions across teams - Work closely with engineers in domain teams, such as our Real-time Risk, Investigations, and Data Fabric teams, to understand their AI integration needs and help them build on platform foundations rather than around them - Keep pace with a rapidly evolving AI landscape: new model capabilities, emerging orchestration patterns, and evaluation techniques. Bring relevant developments to the team's attention and help assess what matters for Elliptic's context You will be a great fit here if you: - Are deeply curious about AI. This goes beyond simple tool use and extends to a passion for the field. You follow new model releases, read about emerging architectures, and find yourself thinking about AI applications unprompted - Take pride in building infrastructure that other engineers love to work with. You care about documentation, reliability, and the experience of your internal customers. - Are comfortable with ambiguity and learning in public. You don't need a perfect brief to get started, and you ask good questions when you're unsure rather than guessing quietly - Think holistically about how complex systems interact. You might not yet have built a production AI platform, but you reason well about dependencies, failure modes, and what makes something extensible versus brittle - Are a collaborative and direct communicator. You share what you know, flag what you don't, and make the engineers around you more effective Our ideal candidate has: - Some hands-on experience building with LLMs or ML systems, whether in production, in side projects, or in an academic context. What matters is that you have gone deep enough to understand how these systems actually behave - Familiarity with AI protocols (MCP, A2A, ACP) with a passion to stay current with emerging trends in the industry - Solid software engineering fundamentals: you write clean, testable code, you think about maintainability, and you understand what it means to build something that will be operated in production - A deep understanding of the context window and an appreciation for its importance in extracting maximum value from the agentic workflow (context rot, compaction etc.) - Exposure to at least one of: API integration and orchestration, data pipeline development, model evaluation or testing, observability and monitoring tooling. Help us understand where your strengths lie and what you’re keen to start exploring - A learning orientation that is evident in how you talk about your work: what you have picked up recently, what you are still figuring out, and what pulled you toward AI engineering in the first place Bonus Points for: - Hands-on experience with frameworks in the LLM or agentic ecosystem: LangChain, LangSmith, Databricks AgentBricks, or similar - Experience with prompt engineering, evaluation dataset design, or LLM output quality assessment - An interest in the crypto and digital assets ecosystem, and alignment with Elliptic's mission of making cryptocurrency safer and more accessible for all - Experience in a regulated or compliance-adjacent domain, or an appreciation of why trustworthiness, explainability, and auditability matter in AI systems that carry real-world weight - Familiarity with MLflow, Databricks ML, or other ML lifecycle tooling JOB BENEFITS > How we work: - Hybrid working and the option to work from almost anywhere for up to 90 days per year - £500 Remote working budget to set up your home office space > Learning & Development: - $1,000 Learning & Development budget to use on anything (agreed with your manager) that contributes to your growth and development > Vacation/ Leave: - Holidays: 25 days of annual leave + bank holidays - An extra day for your birthday - Enhanced parental leave: we provide eligible employees, regardless of gender or whether they become a parent by birth or adoption, 16 weeks fully-paid leave and leave. > Benefits: - Private Health Insurance - we use Vitality! - Full access to Spill Mental Health Support - Life Assurance: we hope you will never need this - but our cover is for 4 times your salary to your beneficiaries - Cycle to Work Scheme", "summaryDescription" : "AI Infrastructure Engineer at Elliptic. Skills: AI Platform, Infrastructure, LLMs, Agentic workflows. Build core components. Maintain core components", "postedDate" : "2026-06-12T00:16:56.417", "createdAt" : "2026-06-12T00:16:56.417", "lastUpdated" : "2026-06-14T22:18:15.957", "ingestTimestamp" : "2026-06-12T00:16:56.417", "mongoId" : "6a2ab17574d8ee00a06d0588", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "75k-100k", "hasSalary" : false, "allSkills" : [ "Model serving infrastructure", "Prompt pipelines", "Evaluation harnesses", "Integration patterns", "Agentic workflows", "Orchestration scaffolding", "Reliability mechanisms", "AI observability", "Tracing model calls", "Token cost tracking", "Latency signals", "Quality signals", "Dashboards", "Alerting", "Prompt tooling", "Prompt versioning", "Prompt testing", "API integration", "Data pipeline development", "Model evaluation", "Observability tooling", "Monitoring tooling", "Software engineering fundamentals", "Context window", "Agentic workflow", "Crypto ecosystem", "Digital assets", "Regulated domain", "Trustworthiness", "Explainability", "Auditability", "ML lifecycle tooling", "Curiosity", "Learning velocity", "Holistic thinking", "Direct communication", "AI Platform", "Infrastructure", "LLMs", "System design", "Prompt engineering", "Evaluation dataset design", "LLM output quality", "AI", "LangChain", "LangSmith", "Databricks AgentBricks", "MLflow", "Databricks ML" ], "skillCount" : 49, "jobCategory" : "engineering", "jobSubcategory" : "engineering", "dataQualityScore" : 0.8888889, "_score" : 672.44574, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2cd86974d8ee00a0a44733", "title" : "AI Platform & Infrastructure Lead", "company" : "Naked Wines", "industry" : "Food & Beverages", "salary" : { "min" : 115000.0, "max" : 165000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for AI Platform & Infrastructure Lead in London, UK, adjusted for lead seniority and e-commerce industry." }, "location" : "Norwich, England, United Kingdom", "locations" : [ "Norwich, England, United Kingdom" ], "timestamp" : "2026-06-16T02:53:15.919", "fingerprint" : "98cfabae2fc8d64f0a89041088eedade4021bb19fafe0ab532aa7d934e7d9328", "source" : "workable", "language" : "en", "applyUrl" : "https://apply.workable.com/j/20248F59D5/apply", "externalId" : "20248F59D5", "industryFunction" : { }, "locationPoint" : "52.62783,1.29834", "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "51.5074456,-0.1277653" }, { "city" : "Norwich", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "52.6285576,1.2923954" } ], "locationText" : "London, England, United Kingdom; Norwich, England, United Kingdom", "employmentType" : "FULL_TIME", "experienceMinYears" : 8, "experienceMaxYears" : 15, "experienceLevel" : "Lead", "technicalSkills" : "AWS, GitLab, Jenkins, Looker, RAG, GenAI, LLMOps", "professionalSkills" : [ "System design", "System thinking", "Business acumen", "Technical communication" ], "hardSkillsList" : [ "AI infrastructure design", "AI infrastructure scaling", "Retrieval pipelines", "Agent observability", "Model gateways", "Data masking", "Policy-based access", "AI service consumption", "Data privacy", "Model deployment", "Defense-in-depth patterns", "Prompt injection defense", "Data leakage defense", "Reference architectures", "Platform enablement" ], "softSkillsList" : [ "Leadership", "Trusted advisor" ], "hardSkills" : [ { "name" : "AI infrastructure design", "level" : "intermediate" }, { "name" : "AI infrastructure scaling", "level" : "intermediate" }, { "name" : "Retrieval pipelines", "level" : "intermediate" }, { "name" : "Agent observability", "level" : "intermediate" }, { "name" : "Model gateways", "level" : "intermediate" }, { "name" : "Data masking", "level" : "intermediate" }, { "name" : "Policy-based access", "level" : "intermediate" }, { "name" : "AI service consumption", "level" : "intermediate" }, { "name" : "Data privacy", "level" : "intermediate" }, { "name" : "Model deployment", "level" : "intermediate" }, { "name" : "Defense-in-depth patterns", "level" : "intermediate" }, { "name" : "Prompt injection defense", "level" : "intermediate" }, { "name" : "Data leakage defense", "level" : "intermediate" }, { "name" : "Reference architectures", "level" : "intermediate" }, { "name" : "Platform enablement", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" }, { "name" : "Trusted advisor" } ], "majorSkills" : "AI Platform, Infrastructure Lead, GenAI, LLMOps", "majorSkillsList" : [ "AI Platform", "Infrastructure Lead", "GenAI", "LLMOps" ], "coreResponsibilities" : "Architect AI infrastructure, Integrate AI tooling, Implement retrieval pipelines, Implement agent observability, Implement model gateways, Develop technical guardrails, Maintain technical guardrails, Define AI standards, Define data privacy standards, Define model deployment standards, Align departmental tools, Architect defense-in-depth patterns, Produce reference architectures, Empower teams to implement Golden Path, Provide strategic guidance, Provide clarity to stakeholders, Provide calm leadership", "teamCollaboration" : "Engineering teams; Senior leadership; Non-technical stakeholders", "domainKnowledge" : "AI/ML; GenAI; LLMOps; RAG; Agentic systems; Vector retrieval; Data privacy; Model deployment; Prompt injection; Data leakage", "domainList" : [ "ai-ml", "genai", "llmops", "rag", "agentic-systems", "vector-retrieval", "data-privacy", "model-deployment", "prompt-injection", "data-leakage" ], "domainSpecificKnowledge" : [ "AI/ML", "GenAI", "LLMOps", "RAG", "Agentic systems", "Vector retrieval", "Data privacy", "Model deployment", "Prompt injection", "Data leakage" ], "toolProficiency" : [ "AWS", "GitLab", "Jenkins", "Looker" ], "communicationSkills" : "Technical communication; Clear recommendations", "documentationSkills" : "Documentation", "continuousLearning" : "Personal development budget", "specialRequirements" : "One visit a month to office", "qualificationsBasic" : "Proven experience designing AI/ML infrastructure, Proven experience scaling AI/ML infrastructure, Familiar with RAG, Familiar with agentic systems, Familiar with LLMOps, Familiar with vector retrieval, Experience building secure systems, Experience meeting data residency requirements, Experience meeting service management requirements, Expertise evaluating AI use cases, Expertise understanding ROI, Expertise assessing implementation trade-offs", "qualificationsPreferred" : "GenAI infrastructure experience", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "In a nutshell, we’re all about making the world of wine a better place. We fund and source directly from independent winemakers to bring customers better quality wine for a better price. No thirsty middlemen as far as the eye can see. It’s a different way of doing things, sure. But it works. We’re one of the UK’s favourite wine clubs, shipping over 1 million (!) cases a year to curious wine lovers. And with an ambitious road ahead, we’ve got no plans on plugging the cork on growth. Our global team (we have offices in the US and Australia, too) is entrepreneurial by nature, obsessive about customer experience and driven by performance. All things that make Naked a great place to grow both personally and professionally. And yes, we like wine. A lot. It takes a village to be Naked. That’s why we’re always on the lookout for eager talent to join the club. And now, our **Technology** team is looking for an **AI Platform & Infrastructure Lead** to join the fun. As we scale our AI initiatives, we are moving from a fragmented landscape of tools to a unified, secure, and developer-friendly \"Golden Path.\" You’ll be the hands-on architect designing the technical standards and infrastructure patterns that make compliant AI usage the default behaviour for the company. So if you’re keen to help us take the guesswork out of enjoying great wine (that’s what we’re passionate about), there’s a Naked welcome pack with your name on it. Together, we’ll take Naked Wines to the next level – and share our not-so-well-kept secret with the world. **Location & Flexible Working **\\- Hybrid: London or Norwich (one visit a month to either office) **Requirements** ### **What you'll do** * **Architect the \"Golden Path\":** Design the end-to-end AI infrastructure that enables teams to adopt AI tooling safely and at speed, integrating seamlessly with our stack (AWS, GitLab, Jenkins, Looker, and more). * **Build Reference Implementations:** Move beyond theory by implementing the first instances of key platform patterns - retrieval pipelines, agent observability harnesses, and model gateways - alongside our engineering teams. * **Governance-as-Code:** Develop and maintain technical guardrails - such as automated data masking and policy-based access control - directly within our CI/CD pipelines. * **Define Standards:** Act as the technical source of truth for AI service consumption, data privacy, and model deployment, ensuring all departmental tools align with our central infrastructure. * **Security & Resilience by Design:** Partner with Security to architect defense-in-depth patterns against modern AI risks like prompt injection and data leakage. * **Platform Enablement:** Produce the reference architectures and documentation that empower other teams to implement the Golden Path across their specific domains. * **Strategic Guidance:** Act as a technical 'trusted advisor' to stakeholders and senior leadership, providing clarity and calm leadership within a landscape of rapid technological change. ### **What you'll bring** * **Architectural Maturity:** Proven experience designing and scaling AI/ML and GenAI infrastructure. You’re familiar with RAG, agentic systems, LLMOps, and vector retrieval. * **System-Level Thinking:** You look beyond the immediate task to understand how platform decisions impact the entire engineering ecosystem and aren't afraid to challenge legacy standards. * **Security First:** You treat security as a first-class engineering concern, with experience building systems that satisfy stringent data residency and service management requirements. * **Business Acumen:** Expertise in evaluating potential AI use cases, understanding ROI, and assessing implementation trade-offs (including when to keep a 'human in the loop'). * **Technical Communication:** You can distill complex requirements into clear, evidence-based recommendations for both engineering and non-technical stakeholders. * **Continuous Curiosity:** You proactively track the evolving AI landscape to ensure our platform remains state-of-the-art and competitive. ### And finally you live by our Naked values: * We are Naked Together - We believe that when people come together, great things get better. That is why we put people at the heart of what we do: our Angels, our Winemakers, our People and our Investors. What makes this work is trust, and we protect it diligently. * We back independence - We believe great things happen when people are free to create and think for themselves. We pride ourselves on challenging the status quo and solving problems independently. * We are bold - We choose courage over comfort and are not afraid to call things as they are. We dream big and take action to turn our ambition into reality - even in the face of uncertainty. * We care about our craft - We have a passion for our craft and strive for excellence in everything we do. We hone our craft continuously and keep on finding ways to do things better. * We choose what’s right - We do right to our people, our planet and our products, and believe everyone can make a difference. We accept the inevitable trade-offs that come with doing the right thing. **Recruitment Process -** Interview & Task > Panel Interview **Benefits** As part of the Naked family, we want you to know we've got your back. Here are a few of the perks you'll enjoy when you join the team… * A competitive salary of £70-£80k pa plus annual bonus opportunity * Personal Healthcare * 26 days holiday and bank holidays (you can buy or sell holiday too) * A £300 annual personal development budget - we're passionate about supporting people to follow their dreams inside or outside of Naked * £450 every year to treat yourself to some of our delicious wines...all in the name of research, of course * We want to do our bit for the community and give everyone paid leave to volunteer * We have wellbeing support and access to mindfulness resources * Enhanced parental leave * We like to surprise and delight you with lovely thoughtful gifts including Naked Wine and lots more... Equal Opportunities At Naked Wines, we recognise the value of diversity and inclusivity in fostering a truly remarkable experience for all our winemakers and customers. Our commitment extends beyond wine to building a workforce that reflects the wide array of perspectives and experiences found across the UK. We believe that embracing diversity in our teams enables us to provide exceptional service and innovation.We are dedicated to ensuring all our employees are treated fairly and equitably at work, with a strong commitment to promoting equity in both physical and mental health for everyone. To achieve this, Naked Wines encourages applications from individuals of disadvantaged socio-economic backgrounds, disabled persons, LGBTQ+ community members, Black, Asian and Minority Ethnic backgrounds, and those with lived experiences of discrimination. Accessibility and Adjustments Naked Wines is committed to providing reasonable adjustments throughout our recruitment process. We strive to be as accommodating as possible to ensure all candidates can participate fully. If you have specific requirements or need adjustments at any stage of the application or interview process, please do not hesitate to get in touch. In your application, feel free to indicate your preferred pronouns (for example - she/her/hers, he/him/his, they/them/theirs, etc)to help us better address and respect your identity throughout the process.", "summaryDescription" : "AI Platform & Infrastructure Lead at Naked Wines. Skills: AI Platform, Infrastructure Lead, GenAI, LLMOps. Architect AI infrastructure. Integrate AI tooling", "postedDate" : "2026-06-10T00:00:00.000", "createdAt" : "2026-06-14T19:25:28.942", "lastUpdated" : "2026-06-16T02:53:15.919", "ingestTimestamp" : "2026-06-14T19:25:28.942", "mongoId" : "6a2cd86974d8ee00a0a44733", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://apply.workable.com/j/20248F59D5", "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "AI infrastructure design", "AI infrastructure scaling", "Retrieval pipelines", "Agent observability", "Model gateways", "Data masking", "Policy-based access", "AI service consumption", "Data privacy", "Model deployment", "Defense-in-depth patterns", "Prompt injection defense", "Data leakage defense", "Reference architectures", "Platform enablement", "Leadership", "Trusted advisor", "AI Platform", "Infrastructure Lead", "GenAI", "LLMOps", "System design", "System thinking", "Business acumen", "Technical communication", "AI/ML", "RAG", "Agentic systems", "Vector retrieval", "Prompt injection", "Data leakage", "AWS", "GitLab", "Jenkins", "Looker" ], "skillCount" : 35, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "mid", "dataQualityScore" : 1.0, "_score" : 660.87634, "daysOld" : 6, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "E-Commerce", "llmIndustryConfidence" : 0.95 }, { "id" : "69164d8e70f0b99d586f289a", "title" : "Sr. Technical Program Manager, Infrastructure", "company" : "Amazon Kuiper", "industry" : "Project/Program/Product Management--Technical, Tech Infrastructure Prgrm Mgmt, alexa and amazon devices", "salary" : { "min" : 133800.0, "max" : 231300.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Bellevue, Washington, USA", "locations" : [ "Bellevue, Washington, USA" ], "certifications" : [ "PMP certificate", "BICSI RCDD certification", "DCDC certification", "OSP certification", "NTS certification", "PSP certifications" ], "timestamp" : "2026-06-15T02:46:44.226", "fingerprint" : "6ba64787cb25ef438e6268dd8baf8c1630e9570eb5638e182d5d71e944a358c0", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3120198/apply", "externalId" : "c0048a86-1a7a-453d-a175-18a7d77b4100", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Bellevue", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6144219,-122.1923370" } ], "locationText" : "Bellevue, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Network systems, Telecommunications, Security systems, Communications distribution", "professionalSkills" : [ "Program management", "Technical leadership", "Stakeholder management", "Risk assessment", "Bid analysis", "Hardware planning", "System acceptance testing" ], "hardSkillsList" : [ "Infrastructure deployment", "Cross-functional programs", "Operational readiness", "Scoping", "Requirements definition", "Technical due diligence", "WAN service feasibility", "Last-mile construction", "Network infrastructure", "Server infrastructure", "Wireless infrastructure", "Security systems deployment", "Facility design", "Permitting", "Construction", "Low voltage integration", "Program management procedures", "Design standards", "Scaling operations", "System acceptance" ], "hardSkills" : [ { "name" : "Infrastructure deployment", "level" : "intermediate" }, { "name" : "Cross-functional programs", "level" : "intermediate" }, { "name" : "Operational readiness", "level" : "intermediate" }, { "name" : "Scoping", "level" : "intermediate" }, { "name" : "Requirements definition", "level" : "intermediate" }, { "name" : "Technical due diligence", "level" : "intermediate" }, { "name" : "WAN service feasibility", "level" : "intermediate" }, { "name" : "Last-mile construction", "level" : "intermediate" }, { "name" : "Network infrastructure", "level" : "intermediate" }, { "name" : "Server infrastructure", "level" : "intermediate" }, { "name" : "Wireless infrastructure", "level" : "intermediate" }, { "name" : "Security systems deployment", "level" : "intermediate" }, { "name" : "Facility design", "level" : "intermediate" }, { "name" : "Permitting", "level" : "intermediate" }, { "name" : "Construction", "level" : "intermediate" }, { "name" : "Low voltage integration", "level" : "intermediate" }, { "name" : "Program management procedures", "level" : "intermediate" }, { "name" : "Design standards", "level" : "intermediate" }, { "name" : "Scaling operations", "level" : "intermediate" }, { "name" : "System acceptance", "level" : "intermediate" } ], "majorSkills" : "Infrastructure program management, Enterprise infrastructure, Technical program management", "majorSkillsList" : [ "Infrastructure program management", "Enterprise infrastructure", "Technical program management" ], "coreResponsibilities" : "Lead infrastructure readiness programs, Develop infrastructure deployment roadmaps, Maintain infrastructure deployment roadmaps, Drive standardization of deployment processes, Drive standardization of technical specifications, Create integrated project schedules, Manage integrated project schedules, Establish program KPIs, Track program KPIs, Provide feasibility assessment, Provide scoping, Provide requirements definition, Lead technical due diligence, Lead risk assessment, Lead programming for infrastructure delivery, Manage WAN service feasibility studies, Manage bid analysis, Manage last-mile construction, Drive network infrastructure design, Drive server infrastructure design, Drive wireless infrastructure design, Drive hardware planning, Drive commissioning, Oversee security systems deployment, Oversee security systems integration, Ensure infrastructure requirements are met, Lead communications distribution design, Lead low voltage integration efforts, Act as technical liaison, Lead quarterly business reviews, Partner with product managers, Partner with engineering teams, Build relationships with cross-functional teams, Maintain relationships with cross-functional teams, Drive evolution of program management procedures, Drive evolution of design standards, Implement best practices for deployment, Implement best practices for scaling, Develop documentation for deployment processes, Maintain documentation for deployment processes, Develop documentation for technical standards, Maintain documentation for technical standards, Lead operational readiness reviews, Lead system acceptance testing", "teamCollaboration" : "Cross-functional teams; Internal engineering teams; Project engineering vendors; Product managers; Facilities teams; Networking teams; Security teams; Operations teams", "projectManagementSkills" : [ "Program management", "Roadmap planning", "Project schedules", "KPIs", "Risk assessment", "Bid analysis" ], "domainKnowledge" : "Enterprise infrastructure; Network systems; Telecommunications; Security systems; Communications distribution; Physical data centers; MDF/IDF spaces; Physical layer telecommunications; WAN circuit delivery; Satellite broadband network", "domainList" : [ "enterprise-infrastructure", "network-systems", "telecommunications", "security-systems", "communications-distribution", "physical-data-centers", "mdf-idf-spaces", "physical-layer-telecommunications", "wan-circuit-delivery", "satellite-broadband-network" ], "domainSpecificKnowledge" : [ "Enterprise infrastructure", "Network systems", "Telecommunications", "Security systems", "Communications distribution", "Physical data centers", "MDF/IDF spaces", "Physical layer telecommunications", "WAN circuit delivery", "Satellite broadband network" ], "communicationSkills" : "Written communication; Verbal communication", "documentationSkills" : "Construction documentation; Deployment processes documentation; Technical standards documentation", "innovationCreativity" : "Creating new solutions", "problemSolvingSkills" : "Root cause analysis; Troubleshooting; Data-driven decision making", "specialRequirements" : "25-50% travel, Travel domestically, Travel internationally, Work within global time zones", "outcomesObjectives" : "Ensure visibility and accountability; Ensure operational readiness; Meet infrastructure requirements", "qualificationsBasic" : "Bachelor's degree in Engineering, Bachelor's degree in Computer Science, Experience communicating results to senior leadership, Experience in automating infrastructure, Experience in deploying infrastructure, Experience in supporting large-scale infrastructure, Experience managing enterprise-level technical infrastructure programs, Experience scaling technical infrastructure operations, Experience leading buildout of physical data centers, Experience leading buildout of MDF/IDF spaces, Experience with physical layer telecommunications, Experience with WAN circuit delivery, Experience developing communications distribution design drawings, Experience developing construction documentation, Working knowledge of network infrastructure architecture, Working knowledge of server infrastructure architecture, Working knowledge of wireless infrastructure architecture, U. S. Citizen", "qualificationsPreferred" : "PMP certificate, Experience influencing internal stakeholders, Experience influencing external stakeholders, Master's degree in Engineering, Master's degree in Computer Science, BICSI RCDD certification, DCDC certification, OSP certification, NTS certification, PSP certifications, Experience in aerospace, Experience in manufacturing, Experience in regulated industries", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Project Kuiper is Amazon’s low Earth orbit satellite broadband network. Its mission is to deliver fast, reliable internet to customers and communities around the world, and we’ve designed the system with the capacity, flexibility, and performance to serve a wide range of customers, from individual households to schools, hospitals, businesses, government agencies, and other organizations operating in locations without reliable connectivity. Export Control : This position requires that the candidate selected be a U.S. Citizen in order to comply with U.S. government-imposed requirements related to the nature of the work and/or where it will be performed. We are seeking a highly experienced technical program manager to drive the development and deployment of critical enterprise infrastructure across our rapidly scaling operations. This role will be instrumental in establishing standardized infrastructure deployment practices, managing complex cross-functional programs, and ensuring operational readiness across multiple facilities and technical environments. A successful candidate is a self-starter who thrives in a start-up environment, has a passion for scaling operations, and possesses a strong background in technology infrastructure program management, network systems, telecommunications, security systems, and communications distribution design and delivery. This role requires 25-50% travel. Key job responsibilities Program Management & Strategy: - Lead end-to-end infrastructure readiness programs across solution development and deployment initiatives - Develop and maintain comprehensive infrastructure deployment roadmaps aligned with business milestones - Drive standardization of infrastructure deployment processes and technical specifications. - Create and manage integrated project schedules across multiple workstreams - Establish and track program KPIs, ensuring visibility and accountability Technical Leadership: - Provide feasibility assessment, scoping, and requirements definition across projects - Lead technical due diligence, risk assessment, and programming for infrastructure delivery - Manage WAN service feasibility studies, bid analysis, and last-mile construction - Drive network, server, and wireless infrastructure design, hardware planning, and commissioning - Oversee security systems deployment and integration - Ensure infrastructure requirements are met during facility design, permitting, and construction - Lead communications distribution design and low voltage integration efforts Stakeholder Management: - Act as technical liaison between internal engineering teams and project engineering vendors - Lead quarterly business reviews with engineering vendors - Partner with product managers and engineering teams on infrastructure systems development - Build and maintain strong relationships with cross-functional teams including facilities, networking, security, and operations Continuous Improvement: - Drive evolution of program management procedures and design standards - Implement best practices for infrastructure deployment and scaling - Develop and maintain documentation for deployment processes and technical standards - Lead operational readiness reviews and system acceptance testing - Establish metrics and reporting frameworks for infrastructure programs A day in the life In this role, you will drive critical infrastructure initiatives that enable Kuiper's ambitious mission by delivering scalable solutions across satellite manufacturing, testing, and deployment facilities. You will be partnering with engineering, operations, supply chain, and other teams to standardize infrastructure deployment, influence technical architecture, and build frameworks for sustainable growth. This position offers a unique opportunity to shape the future of global communications infrastructure while working with advanced technologies in a fast-paced, mission-driven environment. About the team You'll be joining a newly formed infrastructure program team within Enterprise Technology, focused on building and scaling the foundation that enables Kuiper's ambitious mission. Our team combines deep technical expertise with strong program management capabilities to deliver critical infrastructure on time and at scale. We operate with a startup mindset while leveraging Amazon's resources and best practices. Our culture emphasizes ownership, data-driven decision making, and innovation in solving complex problems. We're building something that's never been done before, and we're looking for individuals who are excited about creating new solutions rather than following established playbooks. Basic Qualifications: - Bachelor's degree in Engineering, Computer Science, or a related technical field - Experience communicating results to senior leadership - Experience in automating, deploying, and supporting large-scale infrastructure - Experience managing enterprise-level technical infrastructure programs - Experience scaling technical infrastructure operations - Experience leading the buildout of physical data centers and/or MDF/IDF spaces - Experience with physical layer telecommunications and WAN circuit delivery - Experience developing communications distribution design drawings and construction documentation - Working knowledge of network, server, and wireless infrastructure architecture - Flexibility to travel domestically and internationally, and work within global time zones Preferred Qualifications: - PMP certificate - Experience influencing internal and external stakeholders - Master's degree in Engineering, Computer Science, or related technical field - BICSI RCDD certification - DCDC, OSP, NTS, or PSP certifications - Experience in aerospace, manufacturing, or regulated industries - Excellence in written and verbal communication - Proven ability to lead complex technical initiatives in ambiguous environments - Track record of building scalable operational processes Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $133,800/year in our lowest geographic market up to $231,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.", "summaryDescription" : "Sr. Technical Program Manager, Infrastructure at Amazon Kuiper. Skills: Infrastructure program management, Enterprise infrastructure, Technical program management. Lead infrastructure readiness programs. Develop infrastructure deployment roadmaps", "postedDate" : "2026-06-13T00:56:52.636", "createdAt" : "2026-06-13T00:56:52.636", "lastUpdated" : "2026-06-15T02:46:44.226", "ingestTimestamp" : "2026-06-13T00:56:52.636", "mongoId" : "69164d8e70f0b99d586f289a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3120198/apply", "salaryAnnualMin" : 133800, "salaryAnnualMax" : 231300, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Infrastructure deployment", "Cross-functional programs", "Operational readiness", "Scoping", "Requirements definition", "Technical due diligence", "WAN service feasibility", "Last-mile construction", "Network infrastructure", "Server infrastructure", "Wireless infrastructure", "Security systems deployment", "Facility design", "Permitting", "Construction", "Low voltage integration", "Program management procedures", "Design standards", "Scaling operations", "System acceptance", "Infrastructure program management", "Enterprise infrastructure", "Technical program management", "Program management", "Technical leadership", "Stakeholder management", "Risk assessment", "Bid analysis", "Hardware planning", "System acceptance testing", "Roadmap planning", "Project schedules", "KPIs", "Network systems", "Telecommunications", "Security systems", "Communications distribution", "Physical data centers", "MDF/IDF spaces", "Physical layer telecommunications", "WAN circuit delivery", "Satellite broadband network", "PMP certificate", "BICSI RCDD certification", "DCDC certification", "OSP certification", "NTS certification", "PSP certifications" ], "skillCount" : 48, "jobCategory" : "project-management", "dataQualityScore" : 1.0, "_score" : 658.9842, "daysOld" : 2, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2c7f4c74d8ee00a09550ee", "title" : "Pipeline Construction Inspector", "company" : "WSC", "industry" : "Consulting", "salary" : { "min" : 75000.0, "max" : 110000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Mid-level Pipeline Construction Inspector in San Luis Obispo, United States, adjusted for industry and company size." }, "location" : "San Luis Obispo, California, United States", "locations" : [ "San Luis Obispo", "California", "United States" ], "timestamp" : "2026-06-15T09:23:35.448", "fingerprint" : "2b346054de06ed3a448348419c4872e826bf934ffb9edf4b9bf985abb0990ab6", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/watersystemsconsulting/jobs/8530742002", "externalId" : "8530742002", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Luis Obispo", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "35.3540209,-120.3757160" } ], "locationText" : "San Luis Obispo, California, United States", "professionalSkills" : [ "Construction inspection", "Quality assurance", "Regulatory compliance", "Documentation", "Interpersonal skills" ], "hardSkillsList" : [ "Water infrastructure", "Wastewater infrastructure" ], "hardSkills" : [ { "name" : "Water infrastructure", "level" : "intermediate" }, { "name" : "Wastewater infrastructure", "level" : "intermediate" } ], "majorSkills" : "Construction inspection, Water infrastructure, Wastewater infrastructure", "majorSkillsList" : [ "Construction inspection", "Water infrastructure", "Wastewater infrastructure" ], "coreResponsibilities" : "Conduct on-site inspections, Ensure compliance with plans, Ensure compliance with specifications, Ensure compliance with codes, Ensure compliance with standards, Monitor construction activities, Assess construction activities, Ensure quality, Ensure safety, Ensure permit requirements are met, Maintain detailed records, Maintain accurate records, Prepare daily inspection reports, Provide regular updates, Ensure project adherence to plans, Ensure project adherence to specifications, Ensure project adherence to permitting requirements, Ensure project compliance with SWPPP, Ensure project compliance with MMRP, Address issues, Resolve conflicts, Ensure smooth project execution, Communicate inspection results, Communicate project status, Communicate potential risks, Implement quality assurance measures, Enforce quality assurance measures, Ensure materials meet requirements, Ensure workmanship meets requirements, Ensure construction processes meet requirements", "teamCollaboration" : "Collaborate with project managers; Collaborate with engineers; Collaborate with contractors; Communicate with team members", "domainKnowledge" : "Water infrastructure; Wastewater infrastructure; Civil engineering; Mechanical engineering; Electrical engineering; Instrumentation communication", "domainList" : [ "water-infrastructure", "wastewater-infrastructure", "civil-engineering", "mechanical-engineering", "electrical-engineering", "instrumentation-communication" ], "domainSpecificKnowledge" : [ "Water infrastructure", "Wastewater infrastructure", "Civil engineering", "Mechanical engineering", "Electrical engineering", "Instrumentation communication" ], "communicationSkills" : "Communication; Documentation", "documentationSkills" : "Documentation; Reporting", "specialRequirements" : "Company and insurance requirements for driving eligibility", "outcomesObjectives" : "Deliver outstanding client service; Deliver high-quality results", "qualificationsBasic" : "Previous experience in construction, Construction management experience, Inspection experience, Water and wastewater infrastructure focus, Knowledge of water and wastewater infrastructure design, Knowledge of construction methods, Knowledge of equipment, Knowledge of materials, Knowledge of applicable code requirements, Ability to interpret engineering plans, Ability to interpret specifications, Valid driver’s license", "qualificationsPreferred" : "OSHA training, ISO certifications", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Want to be part of an engineering and strategic communications consulting firm that defines success by the strength of its relationships with its clients and staff? A firm that invests in its people and fosters an entrepreneurial culture that leads to innovation for our clients, communities and environment? If so, please read on. WSC is a premier engineering, hydrogeology, construction management, and communications consulting firm that focuses exclusively on water. Our team of expert engineers and communicators is recognized for delivering successful planning, design, program management, construction management and energy solutions for municipalities, public and private utilities, special districts, energy providers and more throughout California and the Pacific Northwest. WSC is a next generation consulting leader that meets our clients where they are, providing insight, and redefining the possibilities through a high standard for hands-on service, innovation, quality, and visionary leadership. Recognized as one of the fastest growing companies in our business, we are actively seeking to hire a limited term Pipeline Construction Inspector who aligns with our passion for delivering outstanding client service and high-quality results. This position is based in the Central Coast of California. What You Will Do Construction Inspection: Conduct on-site inspections of water and wastewater construction projects to ensure compliance with approved plans, specifications, applicable codes, and industry standards. Monitor and assess construction activities to ensure quality, safety, and permit requirements are met. Documentation and Reporting: Maintain detailed and accurate records of construction activities, inspections, and any deviations from approved plans. Prepare comprehensive daily inspection reports. Provide regular updates to project managers, engineers, and other staff as required. Regulatory Compliance: Ensure that construction projects adhere to all plans, specification, and permitting requirements. Ensure project compliance with all SWPPP and MMRP requirements, as needed. Communication and Coordination: Collaborate with project managers, engineers, contractors, and other stakeholders to address issues, resolve conflicts, and ensure smooth project execution. Communicate effectively with team members to relay inspection results, project status, and potential risks. Quality Assurance: Implement and enforce quality assurance measures to ensure that materials, workmanship, and construction processes meet contract requirements. What You Bring A passion for water, with an emphasis on creating multi-benefit solutions for communities and the environment. Previous experience in construction, construction management. or inspection, with a focus on water and wastewater infrastructure. Deep knowledge of water and wastewater infrastructure design, construction methods, equipment, materials, and applicable code requirements in one or more disciplines including civil, mechanical, electrical and instrumentation Strong communication, documentation, and interpersonal skills. Ability to interpret engineering plans and specifications. OSHA training and ISO certifications preferred. This position requires a valid driver’s license and the ability to meet company and insurance provider requirements for driving eligibility. Pay Range: This is a full-time, non-exempt, hourly position with an anticipated schedule of approximately 40 hours per week. The position is compensated at an hourly rate of $65.00, which meets or exceeds the applicable prevailing wage rate. Who We Are At WSC, we foster a people-centric culture where we care deeply about client relationships and helping our teammates succeed. We believe there are always opportunities to learn, grow, and advance, and we prioritize supporting each other in that process. We are leaders, influencers and innovators. We are passionate about Creating a Better Water Future, integrating engineering, technology and communications to deliver extraordinary value for the communities we serve. We make it easy for you to enjoy the work you love by providing great benefits. With an attractive compensation package including competitive salary, 401(k) plan, company funded ESOP (employee stock ownership plan), employer paid short- and long-term disability, holiday pay, generous paid time off, fitness and health benefits program, we have you covered! Learn more about the benefits we offer Employee Benefits - WSC WSC is committed to growing our network of people, programs, and resources to nurture an inclusive culture. As such, we do not make hiring or other employment-related decisions on the basis of an applicant or employee's race, color, ethnicity, national origin, citizenship, sex (including pregnancy, childbirth, breastfeeding, and related medical conditions), gender, gender identity or expression, age, religion, disability status, sexual orientation, marital status, medical condition, generic information or characteristics, veteran, military or family status, or other classifications protected by applicable federal, state or local anti-discrimination laws.", "summaryDescription" : "Pipeline Construction Inspector at WSC. Skills: Construction inspection, Water infrastructure, Wastewater infrastructure. Conduct on-site inspections. Ensure compliance with plans", "postedDate" : "2026-06-14T04:03:04.962", "createdAt" : "2026-06-14T04:03:04.962", "lastUpdated" : "2026-06-15T09:23:35.448", "ingestTimestamp" : "2026-06-14T04:03:04.962", "mongoId" : "6a2c7f4c74d8ee00a09550ee", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 75000, "salaryAnnualMax" : 110000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Water infrastructure", "Wastewater infrastructure", "Construction inspection", "Quality assurance", "Regulatory compliance", "Documentation", "Interpersonal skills", "Civil engineering", "Mechanical engineering", "Electrical engineering", "Instrumentation communication" ], "skillCount" : 11, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 654.0678, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Engineering", "llmIndustryConfidence" : 0.95 }, { "id" : "69fda4e54c40e2acd1b99a50", "title" : "Principal GTM Specialist, Agentic AI-Led Mainframe Transformation, AWS Transform, AWS WWSO", "company" : "Amazon Web Services, Inc.", "industry" : "Business Merchant Development, Business/Merchant Development, Cloud Computing", "salary" : { "min" : 193700.0, "max" : 262000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "New York, New York, USA", "locations" : [ "New York, New York, USA" ], "timestamp" : "2026-06-15T07:37:52.546", "fingerprint" : "93c3b8e2e480a0d21a14dfe3fa93f2b3975555125bb6da6280934be595955aea", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.jobs/jobs/10412526/apply", "externalId" : "e12550a7-bdbf-4cae-98d2-c763dde847d4", "industryFunction" : { }, "structuredLocations" : [ { "city" : "New York", "state" : "New York", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "40.7127281,-74.0060152" } ], "locationText" : "New York, New York, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Mainframe, Serverless, Containers, Cloud Operations, AI, Bedrock, AgentCore", "professionalSkills" : [ "Go-To-Market strategy", "Business development", "Sales", "Consulting", "Enterprise modernization", "Core modernization", "Business outcomes", "Commercial model" ], "hardSkillsList" : [ "Negotiating agreements", "Executing agreements", "Modernization technologies", "Migration technologies" ], "hardSkills" : [ { "name" : "Negotiating agreements", "level" : "intermediate" }, { "name" : "Executing agreements", "level" : "intermediate" }, { "name" : "Modernization technologies", "level" : "intermediate" }, { "name" : "Migration technologies", "level" : "intermediate" } ], "majorSkills" : "Agentic AI, Mainframe Transformation, GTM Strategy, Enterprise Modernization", "majorSkillsList" : [ "Agentic AI", "Mainframe Transformation", "GTM Strategy", "Enterprise Modernization" ], "coreResponsibilities" : "Own worldwide GTM strategy, Define partner commercial model, Set sales plays, Align cross-functional teams, Build GTM motions, Engage buyers, Connect legacy core extraction, Lead cross-functional initiatives, Translate customer signals, Bring field intelligence back, Own revenue targets, Own pipeline targets, Own referenceable-outcome targets, Deliver monthly business reviews", "teamCollaboration" : "Cross-functional teams; Sales; Partners; SA; ProServe; Marketing; Service teams", "domainKnowledge" : "Agentic enterprise modernization; Financial Services; Automotive; Public Sector; Healthcare; Legacy cores; Mainframe; Mid-range systems; Cloud-native architecture; Core banking decomposition; Claims modernization; Case management; Regulated industries", "domainList" : [ "agentic-enterprise-modernization", "financial-services", "automotive", "public-sector", "healthcare", "legacy-cores", "mainframe", "mid-range-systems", "cloud-native-architecture", "core-banking-decomposition", "claims-modernization", "case-management", "regulated-industries" ], "domainSpecificKnowledge" : [ "Agentic enterprise modernization", "Financial Services", "Automotive", "Public Sector", "Healthcare", "Legacy cores", "Mainframe", "Mid-range systems", "Cloud-native architecture", "Core banking decomposition", "Claims modernization", "Case management", "Regulated industries" ], "communicationSkills" : "Executive presentations; Business outcomes; Data-driven insights", "problemSolvingSkills" : "Solving problems with technology", "outcomesObjectives" : "Revenue generation; Adoption growth; Deliver production outcomes", "qualificationsBasic" : "7+ years developing business agreements, 7+ years working with Business Application Technologies, 7+ years Go-To-Market experience, 7+ years solving problems with technology in Global Financial Services Industry, 7+ years working with Enterprise Application Modernization and Migration technologies", "qualificationsPreferred" : "Founder or executive experience, Practice leader or business unit owner experience, Experience selling to Fortune 1000, Experience selling to Global 2000 organizations", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Are you a customer-obsessed builder with a passion for helping enterprise customers unlock the core systems that run their businesses? Do you have the business acumen, enterprise modernization background, and sales skills needed to position AWS as the platform of choice for agentic enterprise transformation? Do you love building strategic, data-driven businesses at the intersection of AI and legacy core modernization? Join the Worldwide Specialist Organization (WWSO) GTM team as a Principal GTM Specialist. The Worldwide Specialist Organization (WWSO), part of AWS Sales, is responsible for driving revenue, adoption, and growth from the largest and fastest-growing enterprise-level customers, including public sector. We work backwards from our customers' most complex and business-critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. WWSO teams include business development, specialist, and technical solutions architecture. As part of WWSO, you will provide expertise across the entire life cycle of an AWS customer initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #OneTeam. Within WWSO, this position leads GTM strategy for AWS Transform and agentic enterprise modernization, focused on Financial Services. You will define the worldwide GTM framework for this segment, set the partner commercial model, and align cross-functional teams (SA, ProServ, Partner, Service teams) to a unified revenue plan. You will own the motion that extracts and reimagines the business logic locked inside legacy cores, mainframe, mid-range, and adjacent systems, and rebuilds it as cloud-native, AI-ready architecture that unlocks Bedrock and AgentCore at enterprise scale. You will build sales plays that engage Line-of-Business and CFO buyers around business outcomes, claims cycle time, fraud response, settlement speed, rather than platform migrations. You will leverage our partner network of Global Systems Integrators, Nimble SIs, and ISV-to-Delivery partners to deliver production outcomes at speed, not multi-year programs. You will provide critical feedback from customers to inform the AWS Transform product roadmap and partner strategy. In emerging areas, agentic AI in regulated industries, core banking decomposition, claims modernization, benefits and case management, you play a critical role as the \"first in\" team to build the market. When a customer needs to reinvent a business function that runs on legacy core systems, they count on us to innovate with them, compose the right partner and capability stack, and deliver production outcomes at the speed the business actually requires. Key job responsibilities • Own the worldwide GTM strategy and execution for AWS Transform and Agentic Enterprise Modernization, with Financial Services as the anchor vertical and expansion into Automotive, Public Sector, and Healthcare. Define the partner commercial model, sales plays, and cross-functional operating rhythm across Sales, Partners, SA, ProServe, and Marketing. • Build GTM motions that position modernization as a business outcome, engaging CFO, COO, and Line-of-Business buyers around claims cycle time, fraud response, settlement speed, etc.. rather than infrastructure migration. Move the conversation from IT modernization to LoB transformation. • Connect legacy core extraction across mainframe, mid-range, and adjacent estates to Bedrock and AgentCore adoption, giving customers a defined path from locked business logic to AI-ready, autonomous operations. • Lead cross-functional initiatives to open emerging segments, core banking decomposition, claims modernization, benefits and case management, agentic AI in regulated industries, as the \"first in\" team building new markets for AWS Transform. • Translate and bring customer signals and field intelligence back to AWS Transform service teams and Worldwide leadership to shape the product roadmap and partner investment strategy. • Own revenue, pipeline, and referenceable-outcome targets. Deliver monthly business reviews with data-driven insights on pipeline health, partner contribution, and deal velocity. About the team About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Basic Qualifications: - 7+ years of developing, negotiating and executing business agreements experience - 7+ years of working with Business Application Technologies, including, but not limited to End User Compute (EUC), Supply Chain, Contact Center as a Service, Consumer Data Applications, Encrypted Communications, and/or Communication Developer Services experience - 7+ years of Go-To-Market, Business Development, Sales, or Consulting experience - 7+ years of solving problems with technology in the Global Financial Services Industry experience - 7+ years of working with Enterprise Application Modernization and Migration technologies, including, but not limited to, Mainframe, Serverless, Containers, or Cloud Operations experience Preferred Qualifications: - Experience as a founder or executive focused on related segments, or as a practice leader or business unit owner - Experience selling to Fortune 1000 or Global 2000 organizations Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, MA, Boston - 176,100.00 - 238,200.00 USD annually USA, NY, New York - 193,700.00 - 262,000.00 USD annually USA, WA, Seattle - 176,100.00 - 238,200.00 USD annually", "summaryDescription" : "Principal GTM Specialist, Agentic AI-Led Mainframe Transformation, AWS Transform, AWS WWSO at Amazon Web Services, Inc.. Skills: Agentic AI, Mainframe Transformation, GTM Strategy, Enterprise Modernization. Own worldwide GTM strategy. 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relevance, Data pipelines, MLOps, AIOps", "professionalSkills" : [ "System design", "Performance tuning", "Incident management", "Cross-functional collaboration", "Mentoring" ], "hardSkillsList" : [ "Large-scale distributed systems", "Containerization technologies", "CI/CD pipelines", "Monitoring and alerting", "Data processing", "Data storage", "Machine learning frameworks", "Large language models", "Agentic systems", "Search infrastructure", "Distributed systems design", "Data structures", "Algorithms", "System design", "Performance tuning", "Debugging complex systems", "Large-scale data processing", "LLM deployment", "Agentic system deployment", "Search infrastructure deployment", "Production services operation", "Incident management", "On-call rotations", "Vector databases", "Retrieval-augmented generation", "Prompt engineering", "Fine-tuning LLMs", "Distributed databases", "Real-time data processing", "Graph databases", "Natural language processing", "Information retrieval", "Search relevance", "Large-scale data pipelines", "MLOps", "AIOps", "Security best practices", "Performance optimization", "Cost optimization" ], "hardSkills" : [ { "name" : "Large-scale distributed systems", "level" : "intermediate" }, { "name" : "Containerization technologies", "level" : "intermediate" }, { "name" : "CI/CD pipelines", "level" : "intermediate" }, { "name" : "Monitoring and alerting", "level" : "intermediate" }, { "name" : "Data processing", "level" : "intermediate" }, { "name" : "Data storage", "level" : "intermediate" }, { "name" : "Machine learning frameworks", "level" : "intermediate" }, { "name" : "Large language models", "level" : "intermediate" }, { "name" : "Agentic systems", "level" : "intermediate" }, { "name" : "Search infrastructure", "level" : "intermediate" }, { "name" : "Distributed systems design", "level" : "intermediate" }, { "name" : "Data structures", "level" : "intermediate" }, { "name" : "Algorithms", "level" : "intermediate" }, { "name" : "System design", "level" : "intermediate" }, { "name" : "Performance tuning", "level" : "intermediate" }, { "name" : "Debugging complex systems", "level" : "intermediate" }, { "name" : "Large-scale data processing", "level" : "intermediate" }, { "name" : "LLM deployment", "level" : "intermediate" }, { "name" : "Agentic system deployment", "level" : "intermediate" }, { "name" : "Search infrastructure deployment", "level" : "intermediate" }, { "name" : "Production services operation", "level" : "intermediate" }, { "name" : "Incident management", "level" : "intermediate" }, { "name" : "On-call rotations", "level" : "intermediate" }, { "name" : "Vector databases", "level" : "intermediate" }, { "name" : "Retrieval-augmented generation", "level" : "intermediate" }, { "name" : "Prompt engineering", "level" : "intermediate" }, { "name" : "Fine-tuning LLMs", "level" : "intermediate" }, { "name" : "Distributed databases", "level" : "intermediate" }, { "name" : "Real-time data processing", "level" : "intermediate" }, { "name" : "Graph databases", "level" : "intermediate" }, { "name" : "Natural language processing", "level" : "intermediate" }, { "name" : "Information retrieval", "level" : "intermediate" }, { "name" : "Search relevance", "level" : "intermediate" }, { "name" : "Large-scale data pipelines", "level" : "intermediate" }, { "name" : "MLOps", "level" : "intermediate" }, { "name" : "AIOps", "level" : "intermediate" }, { "name" : "Security best practices", "level" : "intermediate" }, { "name" : "Performance optimization", "level" : "intermediate" }, { "name" : "Cost optimization", "level" : "intermediate" } ], "majorSkills" : "Agentic Search, LLMs, Distributed Systems, Search Infrastructure", "majorSkillsList" : [ "Agentic Search", "LLMs", "Distributed Systems", "Search Infrastructure" ], "coreResponsibilities" : "Design and build agentic search infrastructure, Develop and deploy large language models, Implement and optimize search algorithms, Build and operate production services, Develop and maintain CI/CD pipelines, Monitor system performance and reliability, Troubleshoot and resolve production issues, Participate in on-call rotations, Collaborate with cross-functional teams, Mentor junior engineers, Stay up-to-date with the latest research", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Agentic systems; Search infrastructure; Large language models; Distributed systems; Machine learning; Information retrieval; Retrieval-augmented generation; Prompt engineering", "domainList" : [ "agentic-systems", "search-infrastructure", "large-language-models", "distributed-systems", "machine-learning", "information-retrieval", "retrieval-augmented-generation", "prompt-engineering" ], "domainSpecificKnowledge" : [ "Agentic systems", "Search infrastructure", "Large language models", "Distributed systems", "Machine learning", "Information retrieval", "Retrieval-augmented generation", "Prompt engineering" ], "toolProficiency" : [ "Docker", "Kubernetes", "AWS", "Azure", "GCP", "TensorFlow", "PyTorch", "Vector databases" ], "continuousLearning" : "Stay up-to-date with research", "problemSolvingSkills" : "Debugging complex systems; Troubleshoot and resolve production issues", "specialRequirements" : "On-call rotations", "qualificationsBasic" : "5+ years of experience in software development, Experience with large-scale distributed systems, Experience with cloud platforms (AWS, Azure, GCP), Experience with containerization technologies (Docker, Kubernetes), Experience with CI/CD pipelines, Experience with monitoring and alerting tools, Experience with data processing and storage systems, Experience with machine learning frameworks (TensorFlow, PyTorch), Experience with large language models (LLMs), Experience with agentic systems, Experience with search infrastructure, Experience with Python, Experience with Go, Experience with C++, Experience with Java, Experience with distributed systems design, Experience with data structures and algorithms, Experience with system design, Experience with performance tuning, Experience with debugging complex systems, Experience with large-scale data processing, Experience with machine learning model deployment, Experience with LLM deployment, Experience with agentic system deployment, Experience with search infrastructure deployment, Experience with building and operating production services, Experience with incident management, Experience with on-call rotations, Bachelor's degree in Computer Science or related field", "qualificationsPreferred" : "Master's degree or PhD in Computer Science or related field, Experience with agentic search systems, Experience with vector databases, Experience with retrieval-augmented generation (RAG), Experience with prompt engineering, Experience with fine-tuning LLMs, Experience with distributed databases, Experience with real-time data processing, Experience with graph databases, Experience with natural language processing (NLP), Experience with information retrieval, Experience with search relevance, Experience with large-scale data pipelines, Experience with MLOps, Experience with AIOps, Experience with security best practices, Experience with performance optimization, Experience with cost optimization, Experience with cross-functional collaboration, Experience with mentoring junior engineers", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Contribute to the org-wide shift from product-specific search solutions to a composable, agent-native infrastructure foundation that agents and applications build on to locate, search, discover, and recommend resources across heterogeneous enterprise data. * Build and own the infrastructural substrate beneath the agentic search platform, spanning the index engine, the ingestion and enrichment pipeline, and the entity, identity, and feature intelligence that gives content context. Solve the hard problem of keeping index-time enrichments aligned with what agents expect at query time, so retrieval, ranking, and reasoning all build on a consistent foundation. * Build and operate hybrid indexing technology at scale across large clusters, spanning keyword-based sparse-vector indices, embedding-based semantic indices, and emerging semantic-ID indexing driven by next-token prediction. Own the full index lifecycle, and expose clean, unified contracts to the search primitives and recipes that agents compose on top of the corpus. * Design and run high-throughput ingestion and enrichment pipelines that produce a multi-representation, permission-aware corpus at index time. Orchestrate the stages that make content agent-ready, including parsing, chunking, embedding, entity resolution, and access control, and evolve them as new agentic use cases emerge. * Build and operate multi-modal indexing across the full mix of enterprise data, from free text and structured content such as tables to diagrams, images, and audio and video. Represent each modality so it is retrievable through a unified surface, letting agents find the right material regardless of its form or source. * Contribute to a knowledge graph that resolves entities across enterprise data sources, letting agents link disparate resources such as tickets, files, and people through canonical entity relationships. * Improve the performance, scalability, and observability of search, including query latency, indexing throughput, and cluster health, to deliver low-latency, high-quality agentic search experiences. Apply techniques such as vector quantization to balance model quality, retrieval performance, and storage cost. * Own search infrastructure end to end, from intake and design through rollout and ongoing operations, and help shape the search roadmap as the platform grows to support new agents, primitives, and recipes, including needs not yet anticipated. * Drive reliability and operability across the platform through index lifecycle policies, capacity planning, and cluster scaling strategies that keep a growing library of reusable search capabilities healthy in production. This is a highly collaborative, in-person role, working cross-functionally with Search Ranking, ML, and Platform engineering teams to deliver robust, production-grade agentic search capabilities. ## Qualifications * BS or MS in Computer Science or an equivalent engineering background; PhD is a plus. * 2+ years of full-time industry experience. * Hands-on experience with search technologies; proficiency in one or more search technologies such as Lucene, Solr, Elasticsearch, or OpenSearch is required, with additional experience in vector databases being an advantage. * Excited to be part of an in-person team culture, collaborating on-site with colleagues every day. ## Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. [Learn more here](https://careers.servicenow.com/life-at-servicenow#workpersonas). To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [globaltalentss@servicenow.com ](mailto:globaltalentss@servicenow.com)for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2025 Fortune Media IP Limited. All rights reserved. Used under license.", "summaryDescription" : "Staff Agentic Search Infrastructure Engineer at ServiceNow. Skills: Agentic Search, LLMs, Distributed Systems, Search Infrastructure. Design and build agentic search infrastructure. Develop and deploy large language models", "postedDate" : "2026-06-08T22:37:33.000", "createdAt" : "2026-06-16T00:10:44.825", "lastUpdated" : "2026-06-16T08:58:15.548", "ingestTimestamp" : "2026-06-16T00:10:44.825", "mongoId" : "6a305ebdf292fd229cf7371a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 220000, "salaryAnnualMax" : 330000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Large-scale distributed systems", "Containerization technologies", "CI/CD pipelines", "Monitoring and alerting", "Data processing", "Data storage", "Machine learning frameworks", "Large language models", "Agentic systems", "Search infrastructure", "Distributed systems design", "Data structures", "Algorithms", "System design", "Performance tuning", "Debugging complex systems", "Large-scale data processing", "LLM deployment", "Agentic system deployment", "Search infrastructure deployment", "Production services operation", "Incident management", "On-call rotations", "Vector databases", "Retrieval-augmented generation", "Prompt engineering", "Fine-tuning LLMs", "Distributed databases", "Real-time data processing", "Graph databases", "Natural language processing", "Information retrieval", "Search relevance", "Large-scale data pipelines", "MLOps", "AIOps", "Security best practices", "Performance optimization", "Cost optimization", "Agentic Search", "LLMs", "Distributed Systems", "Search Infrastructure", "Cross-functional collaboration", "Mentoring", "Distributed systems", "Machine learning", "Docker", "Kubernetes", "AWS", "Azure", "GCP", "TensorFlow", "PyTorch" ], "skillCount" : 54, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Lead", "dataQualityScore" : 1.0, "_score" : 647.8165, "daysOld" : 7, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ce88d74d8ee00a0a6b17c", "title" : "Senior Data Engineer - Enterprise B2B Marketplace", "company" : "Truelogic", "industry" : "Operations", "salary" : { "min" : 2500000.0, "max" : 4500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Data Engineer in India, adjusted for the technology industry and remote work." }, "location" : "São Paulo", "locations" : [ "São Paulo" ], "timestamp" : "2026-06-15T09:17:13.112", "fingerprint" : "8563074b781dafcf6ea5952f91ce308ff275d320ac0ec89374ed39ce1eb396f7", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/truelogic/e1722f05-97e2-4784-b8f6-78c55e2030b0/application", "externalId" : "e1722f05-97e2-4784-b8f6-78c55e2030b0", "industryFunction" : { }, "structuredLocations" : [ { "workMode" : "remote" } ], "locationText" : "", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, SQL, AWS, Lambda, Airflow, Dbt, Fivetran, Redshift, Sigma", "professionalSkills" : [ "Data modeling", "Pipeline engineering", "Serverless architecture", "Data governance", "Technical leadership" ], "hardSkillsList" : [ "Data warehousing", "Data ingestion", "Data modeling", "Pipeline orchestration", "Serverless computing", "Automated testing", "Monitoring frameworks", "Data governance" ], "hardSkills" : [ { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "Data ingestion", "level" : "intermediate" }, { "name" : "Data modeling", "level" : "intermediate" }, { "name" : "Pipeline orchestration", "level" : "intermediate" }, { "name" : "Serverless computing", "level" : "intermediate" }, { "name" : "Automated testing", "level" : "intermediate" }, { "name" : "Monitoring frameworks", "level" : "intermediate" }, { "name" : "Data governance", "level" : "intermediate" } ], "majorSkills" : "Data pipelines, Data warehousing, Cloud infrastructure, Data governance", "majorSkillsList" : [ "Data pipelines", "Data warehousing", "Cloud infrastructure", "Data governance" ], "coreResponsibilities" : "Guide data platform architecture, Guide scaling strategies, Guide long-term roadmap, Design data pipelines, Lead data pipeline development, Build integrations, Maintain integrations, Develop serverless data services, Develop ingestion layers, Define data warehouse architectures, Define analytical datasets, Implement automated testing, Implement monitoring frameworks, Implement tracing, Mentor data engineers, Mentor data analysts, Drive data governance improvements, Drive documentation improvements", "teamCollaboration" : "Cross-functional stakeholders; Engineering teams; Finance teams; Product teams; Operations teams", "domainKnowledge" : "B2B marketplace; Enterprise analytics; Cloud-native stack; Serverless architecture; Data governance standards", "domainList" : [ "b2b-marketplace", "enterprise-analytics", "cloud-native-stack", "serverless-architecture", "data-governance-standards" ], "domainSpecificKnowledge" : [ "B2B marketplace", "Enterprise analytics", "Cloud-native stack", "Serverless architecture", "Data governance standards" ], "toolProficiency" : [ "Airflow", "Dbt", "Fivetran", "Redshift", "Sigma", "AWS Lambda" ], "documentationSkills" : "Data governance documentation", "problemSolvingSkills" : "Root cause analysis", "qualificationsBasic" : "8+ years experience, Expert dbt, Expert Airflow, Expert Redshift, Expert Fivetran, Expert Sigma, Advanced Python, Expert SQL, Familiarity with AWS Lambda, Cross-functional leadership", "qualificationsPreferred" : "Modern data stack integration", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "ABOUT TRUELOGIC At Truelogic we are a leading provider of nearshore staff augmentation services headquartered in New York. For over two decades, we’ve been delivering top-tier technology solutions to companies of all sizes, from innovative startups to industry leaders, helping them achieve their digital transformation goals. Our team of 600+ highly skilled tech professionals, based in Latin America, drives digital disruption by partnering with U.S. companies on their most impactful projects. Whether collaborating with Fortune 500 giants or scaling startups, we deliver results that make a difference. By applying for this position, you’re taking the first step in joining a dynamic team that values your expertise and aspirations. We aim to align your skills with opportunities that foster exceptional career growth and success while contributing to transformative projects that shape the future. OUR CLIENT Our client operates the premier technology-driven B2B wholesale marketplace for a rapidly expanding compliance-driven industry, serving thousands of brands and retailers across North America. Managing over $4B+ in annual transaction volume—representing more than 40% of its market's domestic wholesale commerce—their platform streamlines complex logistics, order management, and multi-territory client relationships. They are expanding their core data team to modernize enterprise analytics infrastructure and scale the platform that drives operational and financial insights. JOB SUMMARY The Senior Data Engineer is a high-influence technical leadership role responsible for steering the architecture, evolution, and scalability of the enterprise data platform. Partnering cross-functionally with Engineering, Finance, Product, and Operations, you will establish the technical strategy for how data is modeled, orchestrated, and consumed company-wide. This role demands a hands-on technical driver who can build highly resilient serverless data pipelines, modernize legacy ingestion processes, and institute strict data governance and observability standards across a modern cloud-native data stack. RESPONSIBILITIES - Data Platform Evolution: Guide the foundational architecture, scaling strategies, and long-term roadmap of the enterprise data platform. - Pipeline Engineering: Design and lead the development of highly scalable data pipelines using Airflow, dbt, and Python. - Modern Stack Integration: Build and maintain high-throughput integrations across core modern data stack tools, including Fivetran, Redshift, and Sigma. - Serverless Architecture: Develop and optimize serverless data services and ingestion layers leveraging AWS infrastructure (e.g., AWS Lambda). - Advanced Data Modeling: Partner with cross-functional stakeholders to define reliable, performant data warehouse architectures and analytical datasets. - Observability & Reliability: Implement automated testing, rigorous monitoring frameworks, and tracing to maximize pipeline reliability and minimize operational downtime. - Technical Leadership & Governance: Mentor data engineers and analysts on engineering best practices, while driving continuous improvements in data governance and documentation. QUALIFICATIONS AND JOB REQUIREMENTS Must-Have Technical Expectations & Core Skills: - Professional Longevity: 8+ years of proven experience designing and building production-grade data pipelines and large-scale analytics infrastructure. - Transformation & Orchestration: Strong, expert-level background utilizing dbt and Apache Airflow (or highly equivalent orchestration and transformation frameworks). - Data Warehousing & Ecosystems: Extensive experience with modern data warehouse architecture, specifically scaling and optimizing platforms like Amazon Redshift, alongside tools like Fivetran and Sigma. - Engineering Stack: Advanced Python programming capabilities for complex pipeline creation, automation scripts, and serverless data processing. - Data Mastery: Expert-level SQL skills with deep experience modeling massive, complex datasets for high-performance extraction. - Cloud Infrastructure: Deep practical familiarity with AWS cloud ecosystems, specifically deploying serverless computing architectures (e.g., Lambda). - Cross-Functional Leadership: Demonstrated capability to lead high-stakes technical initiatives, align diverse stakeholders, and modernize legacy workflows with high autonomy. WHAT WE OFFER - 100% Remote Work: Enjoy the freedom to work from the location that helps you thrive. All it takes is a laptop and a reliable internet connection. - Highly Competitive USD Pay: Earn an excellent, market-leading compensation in USD, that goes beyond typical market offerings. - Paid Time Off: We value your well-being. Our paid time off policies ensure you have the chance to unwind and recharge when needed. - Work with Autonomy: Enjoy the freedom to manage your time as long as the work gets done. Focus on results, not the clock. - Work with Top American Companies: Grow your expertise working on innovative, high-impact projects with Industry-Leading U.S. Companies. WHY YOU’LL LIKE WORKING HERE - A Culture That Values You: We prioritize well-being and work-life balance, offering engagement activities and fostering dynamic teams to ensure you thrive both personally and professionally. - Diverse, Global Network: Connect with over 600 professionals in 25+ countries, expand your network, and collaborate with a multicultural team from Latin America. - Team Up with Skilled Professionals: Join forces with senior talent. All of our team members are seasoned experts, ensuring you're working with the best in your field. Apply now!", "summaryDescription" : "Senior Data Engineer - Enterprise B2B Marketplace at Truelogic. Skills: Data pipelines, Data warehousing, Cloud infrastructure, Data governance. Guide data platform architecture. Guide scaling strategies", "createdAt" : "2026-06-14T02:41:04.749", "lastUpdated" : "2026-06-15T09:17:13.112", "ingestTimestamp" : "2026-06-14T02:41:04.749", "mongoId" : "6a2ce88d74d8ee00a0a6b17c", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Data warehousing", "Data ingestion", "Data modeling", "Pipeline orchestration", "Serverless computing", "Automated testing", "Monitoring frameworks", "Data governance", "Data pipelines", "Cloud infrastructure", "Pipeline engineering", "Serverless architecture", "Technical leadership", "B2B marketplace", "Enterprise analytics", "Cloud-native stack", "Data governance standards", "Airflow", "Dbt", "Fivetran", "Redshift", "Sigma", "AWS Lambda" ], "skillCount" : 23, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 645.61523, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ac42d74d8ee00a06fd068", "title" : "Enterprise Account Executive", "company" : "Algolia", "industry" : "Technology", "salary" : { "min" : 120000.0, "max" : 180000.0, "currency" : "GBP", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Enterprise Account Executive in London, UK, adjusted for the technology industry and company size." }, "location" : "London, England, United Kingdom", "locations" : [ "London", "England", "United Kingdom" ], "timestamp" : "2026-06-14T23:20:16.168", "fingerprint" : "dac92016f52dff153af44ba04a22a905f317425cfcfcd4f78bbe76d273a158b0", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/algolia/jobs/6014522004", "externalId" : "6014522004", "industryFunction" : { }, "structuredLocations" : [ { "city" : "London", "state" : "England", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "51.5074456,-0.1277653" }, { "city" : "Manchester", "country" : "United Kingdom", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "53.4424618,-2.2324547" } ], "locationText" : "London, England, United Kingdom; Manchester, United Kingdom", "experienceMinYears" : 10, "experienceMaxYears" : 99, "experienceLevel" : "Executive", "technicalSkills" : "AI/ML, Generative AI", "professionalSkills" : [ "Strategic instincts", "Consultative mindset", "Territory strategy", "Account strategy", "ROI analysis", "Forecasting", "MEDDPICC" ], "hardSkillsList" : [ "Sales pipeline management", "Opportunity management", "Value articulation", "Business value translation", "Buyer risk profiling", "Partner ecosystem leverage" ], "softSkillsList" : [ "Grit", "Trust", "Candid", "Care", "Humility" ], "hardSkills" : [ { "name" : "Sales pipeline management", "level" : "intermediate" }, { "name" : "Opportunity management", "level" : "intermediate" }, { "name" : "Value articulation", "level" : "intermediate" }, { "name" : "Business value translation", "level" : "intermediate" }, { "name" : "Buyer risk profiling", "level" : "intermediate" }, { "name" : "Partner ecosystem leverage", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Grit" }, { "name" : "Trust" }, { "name" : "Candid" }, { "name" : "Care" }, { "name" : "Humility" } ], "majorSkills" : "Enterprise SaaS sales, AI-driven digital transformation, Generative AI, Agentic automation", "majorSkillsList" : [ "Enterprise SaaS sales", "AI-driven digital transformation", "Generative AI", "Agentic automation" ], "coreResponsibilities" : "Own enterprise pipeline, Manage enterprise pipeline, Accelerate enterprise pipeline, Drive inbound opportunities, Drive outbound opportunities, Position generative AI capabilities, Position agentic capabilities, Develop territory strategies, Develop account strategies, Expand existing accounts, Identify strategic growth opportunities, Identify commercial growth opportunities, Generate new enterprise projects, Self-source high-value meetings, Network within communities, Leverage partner ecosystems, Partner with Solutions Engineering, Build bespoke demos, Build proofs-of-value, Build ROI analyses, Forecast accurately, Collaborate cross-functionally", "teamCollaboration" : "Cross-functional collaboration; Solutions Engineering partnership; Customer Success collaboration; Legal collaboration; Marketing collaboration; Partner collaboration", "domainKnowledge" : "AI-first search; Agentic automation; Composable architecture; Generative models; Agentic tools; AI relevance", "domainList" : [ "ai-first-search", "agentic-automation", "composable-architecture", "generative-models", "agentic-tools", "ai-relevance" ], "domainSpecificKnowledge" : [ "AI-first search", "Agentic automation", "Composable architecture", "Generative models", "Agentic tools", "AI relevance" ], "communicationSkills" : "Executive communication; Technical communication", "problemSolvingSkills" : "Problem-solving capability", "outcomesObjectives" : "Improve engagement; Improve business outcomes", "qualificationsBasic" : "5+ years enterprise SaaS sales experience, Track record of closing complex deals, Experience in digital transformation, Experience in AI/ML, Experience in search/commerce domains, Outbound sales capability, Modern prospecting skills, Comfort leading with insight", "qualificationsPreferred" : "Experience selling platforms with usage-based pricing, Experience selling AI-first capabilities, Experience selling composable architectures, Comfort discussing technical architecture, Comfort discussing AI relevance", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "At Algolia, we’re proud to be a pioneer and market leader in AI Search, empowering 17,000+ businesses to deliver blazing-fast, predictive search and browse experiences at internet scale. Every week, we power over 30 billion search requests — four times more than Microsoft Bing, Yahoo, Baidu, Yandex, and DuckDuckGo combined. In 2021, we raised $150 million in Series D funding, quadrupling our valuation to $2.25 billion. This strong foundation enables us to keep investing in our market-leading platform and serving incredible customers like Under Armour, PetSmart, Stripe, Gymshark, and Walgreens. At Algolia, we are on a mission to help businesses connect their end-users with what matters most, in milliseconds. As the leader in AI-powered Search and Discovery, we’re driving the next frontier of digital experiences - where generative AI, adaptive relevance, and agentic workflows help enterprises move beyond traditional search into truly intelligent, self-optimising discovery at scale. As an Enterprise Account Executive, you’ll play a pivotal role in bringing these innovations to life for Global 2000 organisations. You won’t just sell a product - you’ll guide customers through a transformation where algorithms act as strategic copilots, delivering contextual recommendations, predictive experiences, and AI-assisted user journeys that improve engagement and business outcomes. You will own complex, high-impact relationships, lead multi-stakeholder buying cycles, and work cross-functionally to articulate the value of AI-first search, agentic automation, and composable architecture. This role demands strategic instincts, a consultative mindset, and the ability to translate AI innovation into measurable business value. You are a builder, a challenger, and a trusted advisor. You thrive in dynamic environments and know how to position Algolia as a key enabler of AI-driven digital transformation - not just another line item in a stack. YOUR ROLE WILL CONSIST OF: Owning, managing, and accelerating an enterprise pipeline Driving inbound and outbound opportunities through complex, multi-threaded sales cycles to closed-won Positioning Algolia’s generative AI and agentic capabilities to executives and technical champions - showing how real-time relevance, predictive personalisation, and autonomous search assistants deliver business value Developing territory and account strategies across your portfolio Expanding existing accounts by identifying opportunities for strategic and commercial growth Generating new enterprise projects by self-sourcing high-value meetings, networking within communities, and leveraging partner ecosystems Partnering with Solutions Engineering to build bespoke demos, proofs-of-value, and ROI analyses that highlight impact beyond traditional search metrics Forecasting accurately with disciplined methodologies (MEDDPICC) and a deep understanding of decision drivers and buyer risk profiles Collaborating cross-functionally (SDRs, Solutions Engineers, Customer Success, Legal, Marketing, Partners) to align execution with business outcomes and long-term enterprise value YOU MIGHT BE A FIT IF YOU HAVE: 5+ years of enterprise SaaS sales experience, with a strong track record of closing complex deals - especially in digital transformation, AI/ML, or search/commerce domains A deep interest in generative AI, machine learning-enabled customer experiences, and how agentic systems unlock competitive advantage Proven success selling into large, multi-department organisations with complex evaluation criteria and dispersed stakeholder influence Familiarity with selling adjacent solutions or ability to quickly learn technical differentiation and articulate it to technical and executive stakeholders Strong outbound sales capability, modern prospecting skills, and comfort leading with insight Experience working with strategic partners (consultancies, SIs, ISVs) to co-build opportunities NICE TO HAVE: Experience selling platforms with usage-based pricing, AI-first capabilities, or composable architectures Understanding of how generative models and agentic tools are used in commerce, discovery, and digital engagement Comfort discussing technical architecture and AI relevance with technical decision makers A curious, growth-oriented approach with the ability to balance strategic vision and execution rigor A passion for building new ground - especially where cutting-edge AI meets real business outcomes #LI-Hybrid Algolia does not discriminate on the basis of race, color, religion, sex, age, national origin, military status, veteran status, disability status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. The annual total cash compensation range (base salary and commission) for this role reflects market pay data within this location. The exact compensation offered for this role may vary depending on specific location and job-related knowledge, technical skills, and experience; and is only one part of our Total Rewards philosophy to compensate and recognize employees for their work. On-Target Earnings Pay Range £148,500—£206,000 GBP FLEXIBLE WORKPLACE STRATEGY: Algolia’s flexible workplace model is designed to empower all Algolians to fulfill our mission to power search and discovery with ease. We place an emphasis on an individual’s impact, contribution, and output, over their physical location. Algolia is a high-trust environment and many of our team members have the autonomy to choose where they want to work and when. We have a global presence with offices in Paris, NYC, London, Sydney and Bucharest, however we also offer many of our team members the option to work remotely either as fully remote or hybrid-remote employees. Positions listed as \"Remote\" are only available for remote work within the specified country. Positions listed within a specific city are only available in that location - depending on the role it may be available with either a hybrid-remote or in-office schedule. WE’RE LOOKING FOR SOMEONE WHO CAN LIVE OUR VALUES: GRIT - Problem-solving and perseverance capability in an ever-changing and growing environment. TRUST - Willingness to trust our co-workers and to take ownership. CANDOR - Ability to receive and give constructive feedback. CARE - Genuine care about other team members, our clients and the decisions we make in the company. HUMILITY - Aptitude for learning from others, putting ego aside. We’re looking for talented, passionate people to help build the world’s best search and discovery technology. We value autonomy, diversity, and collaboration. We’re committed to creating an inclusive workplace where everyone is respected and supported—regardless of race, age, ancestry, religion, sex, gender identity, sexual orientation, marital status, color, veteran status, disability, or socioeconomic background. IMPORTANT NOTICE FOR CANDIDATES - Recruitment Fraud Notice We’ve recently seen an increase in recruitment scams targeting job seekers. To help protect yourself, please keep the following in mind: Our open positions may appear on third-party job boards, but the best way to apply safely is directly through our careers page. All genuine communication from Algolia will come from an @algolia.com email address. If you receive an email from someone claiming to work at Algolia who does not have an @algolia.com email address, please do not respond or share any personal information. We’ll never ask for payments, purchases, or financial details during the hiring process. READY TO APPLY? If you share our values and our enthusiasm for building the world’s best search & discovery technology, we’d love to review your application!", "summaryDescription" : "Enterprise Account Executive at Algolia. Skills: Enterprise SaaS sales, AI-driven digital transformation, Generative AI, Agentic automation. Own enterprise pipeline. 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Pawtucket, Rhode Island, United States", "employmentType" : "FULL_TIME", "experienceLevel" : "Manager", "technicalSkills" : "Middleware, IPaaS, API-based integration, Event-based integration, Message-based integration, File-based ingestion, ELT, Data pipeline patterns, Informatica, IICS, Boomi, MuleSoft, Azure Integration Services, Fivetran, Dbt, Snowflake, ERP, CRM, Data warehouse, Master data management, Veeva CRM, Veeva Vault, EDC, LIMS, EQMS, Dotmatics, ELN, HRIS, HCM, CLM, Concur, Adaptive Planning, Oracle Fusion, SAP S/4HANA, Workday, ServiceNow", "professionalSkills" : [ "Enterprise integration", "Data engineering", "Architecture", "Governance", "Vendor management", "Cross-functional leadership", "System design", "Data flow design", "Interface specification", "Transformation patterns", "Monitoring practices", "Alerting practices", "Runbook development", "Documentation standards", "Strategic architecture", "Pragmatic delivery", "Operating models" ], "hardSkillsList" : [ "Data pipeline development", "Integration platform management", "System integration", "Data flow management", "API integration", "Message queuing", "File transfer", "ETL development", "Data warehousing", "Master data management", "Data governance", "Data quality management", "System validation", "Regulatory compliance" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Data pipeline development", "level" : "intermediate" }, { "name" : "Integration platform management", "level" : "intermediate" }, { "name" : "System integration", "level" : "intermediate" }, { "name" : "Data flow management", "level" : "intermediate" }, { "name" : "API integration", "level" : "intermediate" }, { "name" : "Message queuing", "level" : "intermediate" }, { "name" : "File transfer", "level" : "intermediate" }, { "name" : "ETL development", "level" : "intermediate" }, { "name" : "Data warehousing", "level" : "intermediate" }, { "name" : "Master data management", "level" : "intermediate" }, { "name" : "Data governance", "level" : "intermediate" }, { "name" : "Data quality management", "level" : "intermediate" }, { "name" : "System validation", "level" : "intermediate" }, { "name" : "Regulatory compliance", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Enterprise integration, Data engineering, Middleware, Data pipelines", "majorSkillsList" : [ "Enterprise integration", "Data engineering", "Middleware", "Data pipelines" ], "coreResponsibilities" : "Manage implementation of integration capabilities, Manage maturation of integration capabilities, Manage implementation of data engineering capabilities, Manage maturation of data engineering capabilities, Partner with leaders to define roadmap, Partner with leaders to maintain roadmap, Evaluate integration platforms, Select integration platforms, Implement integration platforms, Govern integration platforms, Evaluate ELT platforms, Select ELT platforms, Implement ELT platforms, Govern ELT platforms, Design integrations between systems, Oversee integrations between systems, Design data pipelines between systems, Oversee data pipelines between systems, Establish integration standards, Establish data contracts, Establish interface specifications, Establish transformation patterns, Establish naming conventions, Establish monitoring practices, Establish alerting practices, Establish runbooks, Establish documentation standards, Ensure system designs are consistent, Ensure data-flow designs are consistent", "teamCollaboration" : "Partner with IT leaders; Partner with business leaders; Collaborate with Architecture Review Board; Collaborate with business teams; Collaborate with technical teams; Collaborate with Quality teams; Collaborate with Security teams; Collaborate with vendor teams", "projectManagementSkills" : [ "Roadmap planning", "Agile", "PMP", "ITIL" ], "domainKnowledge" : "Neuroscience; Drug discovery; Clinical development; Commercialization; Ion channel biology; Human genetics; Life sciences systems; GxP systems; 21 CFR Part 11; HIPAA; GDPR; SOX", "domainList" : [ "neuroscience", "drug-discovery", "clinical-development", "commercialization", "ion-channel-biology", "human-genetics", "life-sciences-systems", "gxp-systems", "21-cfr-part-11", "hipaa", "gdpr", "sox" ], "domainSpecificKnowledge" : [ "Neuroscience", "Drug discovery", "Clinical development", "Commercialization", "Ion channel biology", "Human genetics", "Life sciences systems", "GxP systems", "21 CFR Part 11", "HIPAA", "GDPR", "SOX" ], "toolProficiency" : [ "Informatica", "IICS", "Boomi", "MuleSoft", "Azure Integration Services", "Fivetran", "Dbt", "Snowflake", "Veeva CRM", "Veeva Vault", "Dotmatics", "ELN", "Oracle Fusion", "SAP S/4HANA", "Workday", "ServiceNow" ], "communicationSkills" : "Cross-functional communication; Stakeholder alignment; Simplify technical concepts", "documentationSkills" : "Documentation standards; Runbooks", "continuousLearning" : "Training; Learning & Development program; Tuition Assistance program", "problemSolvingSkills" : "Problem-solving skills; Simplify complex technical concepts", "qualificationsBasic" : "Minimum 2 days per week in office", "qualificationsPreferred" : "Master data management experience is a plus, Data governance experience is a plus, Data stewardship experience is a plus, Metadata experience is a plus, Data lineage experience is a plus, Data cataloging experience is a plus, Data quality experience is a plus, MDM platform implementation experience is a plus, Computer Systems Assurance preferred, GxP systems validation preferred, SDLC preferred, 21 CFR Part 11 preferred, HIPAA preferred, GDPR preferred, SOX preferred, Audit trails preferred, Data integrity preferred, Role-based access controls preferred, Project management certifications are a plus, Agile certifications are a plus, PMP certifications are a plus, ITIL certifications are a plus, Cloud certifications are a plus, Data certifications are a plus, Integration platform certifications are a plus", "remoteFriendly" : false, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Who We Are: Xenon Pharmaceuticals (NASDAQ:XENE https://www.nasdaq.com/market-activity/stocks/xene) is a neuroscience-focused biopharmaceutical company dedicated to drug discovery, clinical development, and commercialization of life-changing therapeutics for patients in need. We are looking for great people who thrive in a respectful, collaborative, inclusive, and productive culture to join the Xenon team. What We Do: We are advancing an exciting product pipeline https://xenon-pharma.com/pipeline to address indications with high unmet medical need, including epilepsy, depression and pain. Our Phase 3 azetukalner program represents the most advanced, clinically validated potassium channel modulator in late-stage clinical development for multiple indications. In March 2026, we announced positive topline data from our Phase 3 X-TOLE2 study of azetukalner in focal onset seizures (FOS), and we anticipate submitting a New Drug Application to the Food and Drug Administration in the third quarter of 2026. Our Phase 3 epilepsy program also includes a second FOS study, X-TOLE3, which would support regulatory submissions outside the U.S., and the X-ACKT study in primary generalized tonic-clonic seizures, which would support regulatory submissions for an additional epilepsy indication. We also have multiple Phase 3 azetukalner clinical trials underway in major depressive disorder (MDD) and bipolar depression (BPD), based on topline data from our Phase 2 X-NOVA clinical trial. In addition, we are proud of our strong heritage in human genetics, deep understanding of ion channel biology, and expertise in novel chemistries to enable potent, selective ion channel targeting. We continue to advance an early-stage pipeline of novel therapeutic candidates, including Phase 1 studies for XEN1701 (targeting Nav1.7) and XEN1120 (targeting Kv7), which are important pain targets. Backed by a strong balance sheet to support our growth plans, we continue to build a fully integrated, premier neuroscience company with strong discovery, clinical development, corporate, and commercial operations. About the Role: We are seeking a Senior Manager/Associate Director, Enterprise Integration & Data Engineering to join our Information Technology (IT) team. The position will help lead the design, implementation, and ongoing operation of Xenon’s enterprise integration, middleware, and data engineering capabilities. This individual will partner with leaders across IT, Commercial, Medical, Finance, Supply Chain, Clinical Development, Research, and Quality, and external partners to establish scalable, secure, and compliant data flows across Xenon’s enterprise application and analytics ecosystem. This role will be a key enabler of Xenon’s growth and commercialization readiness, helping connect core platforms such as ERP, CRM, data warehouse, master data management, clinical and research systems, quality systems, and external partner networks. The successful candidate will combine hands-on technical depth with strong architecture, governance, vendor management, and cross-functional leadership skills. This position reports to the Director, Data Architecture & Engineering and will be based out of Boston, MA, USA in our Needham office. The level of the position will be commensurate with the candidate’s education and industry experience. This role is a hybrid position, requiring a minimum of 2 days per week in the office. RESPONSIBILITIES: - Manage the implementation and maturation of Xenon’s enterprise integration and data engineering capabilities, including middleware/iPaaS, API-based integration, event/message-based integration, file-based ingestion, and ELT/data pipeline patterns. - Partner with IT and business leaders to define and maintain an enterprise integration roadmap aligned to ERP, Commercial, Medical, Clinical, Research, Quality, MDM, and data warehouse priorities. - In consultation with assigned stakeholders, evaluate, select, implement, and govern integration and ELT platforms such as Informatica/IICS, Boomi, MuleSoft, Azure Integration Services, Fivetran, dbt, Snowflake, or similar technologies. - Design and oversee integrations and data pipelines between internal and external systems including ERP, Veeva CRM/Vault, commercial data providers, patient services platforms, EDC/clinical systems, safety systems, LIMS, eQMS, Dotmatics/ELN, HRIS/HCM, CLM, Concur, Adaptive Planning, banks, CDMOs/CMOs, 3PLs, and other partners. - Establish reusable integration standards, data contracts, interface specifications, transformation patterns, naming conventions, monitoring/alerting practices, runbooks, and documentation standards. - Collaborate with Xenon’s Architecture Review Board to ensure system and data-flow designs are consistent with company standards for security, infrastructure, data architecture, privacy, and operational supportability. - Partner with business data owners and data stewards to establish and maintain effective data governance including master data management, data quality, metadata, lineage, cataloging, access controls, and common data definitions across domains. - Provide technical leadership for data models, ELT transformations, curated data layers, and “gold” datasets that enable trusted analytics, self-service reporting, AI/ML, and operational decision-making. - Ensure integration and data engineering solutions are designed with appropriate controls for GxP, SOX, HIPAA, GDPR, 21 CFR Part 11, auditability, data integrity, and role-based access, as applicable. - Provide technical guidance and support for Computer Systems Assurance (CSA), SDLC, regulatory/risk assessment, testing, validation, and change control deliverables for regulated systems and data flows. - Develop and manage the ongoing support model for integrations and data pipelines, including onboarding and managing qualified implementation partners and service providers. - Ensure ongoing compliance with Xenon procedures including Change Management, Incident Management, Problem Management, SaaS Release Management, and other applicable IT operating processes. - Monitor integration and pipeline performance, manage operational issues to resolution, drive root cause analysis, and lead continuous improvement of platform reliability, scalability, cost efficiency, and support processes. - Translate business requirements into practical integration architecture, technical design, delivery plans, test strategies, and sustainable operating procedures. - Lead, mentor, or coordinate internal and external data engineers, integration developers, analysts, and vendor resources as the capability grows. - Act in accordance with Company policies, including, for example, the Code of Business Conduct and Ethics, and ensure policies are understood and followed by direct reports, if any. - Some international travel may be required. - Other duties as assigned. QUALIFICATIONS: - A bachelor’s degree or advanced degree in Information Systems, Computer Science, Data Engineering, Engineering, Business Administration, with a minimum of 7-10 year’s prior experience with enterprise integration, data engineering, middleware, cloud data platform, analytics platform, or enterprise applications experience; Experience in a corporate IT environment is preferred. Related experience with service and/or solution providers is also relevant. - Experience in Life Sciences, pharmaceutical, biotechnology, healthcare, or another regulated industry is preferred. Direct pharma/biotech experience is valuable but not required if the candidate demonstrates strong enterprise integration, data engineering, cloud data platform. - Proven experience designing and delivering enterprise integrations, API integrations, batch/file-based interfaces, ELT/ETL pipelines, data orchestration, data quality checks, monitoring, and production support processes. - Hands-on experience with one or more integration or data platforms such as Informatica/IICS, Boomi, MuleSoft, Azure Integration Services, Fivetran, dbt, Snowflake, Databricks, or similar technologies. - Strong understanding of cloud data warehouse and analytics architectures, including source-to-target mapping, transformation logic, curated data layers, semantic models, and BI/analytics consumption patterns. - Experience with master data management, data governance, data stewardship, metadata, lineage, data cataloging, and data quality practices; MDM platform implementation experience is a plus. - Experience integrating enterprise SaaS platforms and life-sciences systems such as ERP (Oracle Fusion or SAP S/4HANA), Veeva, Workday/HCM, CLM, Concur, Adaptive Planning, ServiceNow, eQMS, LIMS, EDC, ELN, clinical data repositories, or commercial data platforms. - Experience with Computer Systems Assurance, GxP systems validation, SDLC, 21 CFR Part 11, HIPAA, GDPR, SOX, audit trails, data integrity, and role-based access controls is preferred. - Ability to balance strategic architecture with pragmatic delivery in a growing, fast-paced organization; comfortable building capability, standards, and operating models from the ground up. - Experience managing external consultants, implementation partners, managed service providers, and/or application service providers. - Excellent communication and coordination skills across business, technical, Quality, Security, and vendor teams. - Ability to manage multiple priorities, lead through ambiguity, and drive decisions with appropriate documentation and stakeholder alignment. - Strong problem-solving skills, attention to detail, and ability to simplify complex technical concepts for non-technical audiences. - Project management experience; Agile, PMP, ITIL, cloud, data, or integration platform certifications are a plus. Our Total Rewards program includes base salary, target bonus, and stock options, as well as a full range of benefits including medical, dental, vision, short-& long-term disability, accidental death & dismemberment, and life insurance programs, Employee Assistance Program, travel insurance, and retirement savings programs with company matching contributions. Xenon encourages time to rest and re-charge through vacation, personal days, sick days, and an end-of-year company shutdown. Xenon highly values employee development and has an expanding Training, Learning & Development program, including a Tuition Assistance program for advanced degrees.", "summaryDescription" : "Senior Manager/Associate Director, Enterprise Integration & Data Engineering at Xenon Pharmaceuticals. Skills: Enterprise integration, Data engineering, Middleware, Data pipelines. Manage implementation of integration capabilities. 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Cross-functionally with Security; Cross-functionally with business teams", "domainKnowledge" : "Enterprise administration; Agentic systems; ITSM; Zero Trust principles; RBAC expectations; Compliance frameworks; SOC 2; ISO 27001; FedRAMP; NIST", "domainList" : [ "enterprise-administration", "agentic-systems", "itsm", "zero-trust-principles", "rbac-expectations", "compliance-frameworks", "soc-2", "iso-27001", "fedramp", "nist" ], "domainSpecificKnowledge" : [ "Enterprise administration", "Agentic systems", "ITSM", "Zero Trust principles", "RBAC expectations", "Compliance frameworks", "SOC 2", "ISO 27001", "FedRAMP", "NIST" ], "communicationSkills" : "Explain technical concepts", "problemSolvingSkills" : "Problem-solving skills", "qualificationsBasic" : "Experience building production software, Experience designing interfaces for complex operational products, Track record of turning ambiguous operational problems into clear products, Solid backend engineering fundamentals, Experience building internal platforms, Judgment around security and access boundaries, Excellent stakeholder management skills, Clear and concise communication skills, Analytical and problem-solving skills", "qualificationsPreferred" : "Enterprise SaaS administration experience, Identity systems experience, Privileged operational tooling experience, Building AI-assisted support systems experience, Ticketing systems experience, Request routing experience, Approval flows experience, Operational case management experience, Designing reusable toolsets experience, Familiarity with compliance frameworks", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About the Team OpenAI’s Platform and Infrastructure Engineering organization advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient technology solutions. Our team builds and maintains robust infrastructure that safeguards OpenAI’s data and systems while ensuring employees are well-equipped and seamlessly connected. By prioritizing security, reliability, and user-centric solutions, we empower OpenAI employees to drive impactful AI research, corporate operations, and product innovation. About the Role As a Software Engineer: Internal Applications, Enterprise, you will build internal products that make technology support and administration safer, faster, and less dependent on manual intervention. You will help reduce reliance on broadly privileged human actions, turn recurring technology problems into paved paths, and build agentic systems that can help resolve tickets end to end. A core part of the role is building the interfaces that bring employees, AI agents, and human responders together in a shared ITSM experience, with the right context, controls, and handoffs at each step. We are seeking engineers who enjoy working across frontend and backend layers on ambiguous, high-leverage enterprise problems. You should bring strong product judgment, solid backend engineering fundamentals, and an interest in building software that changes how technology support, system administration, and agent-assisted operations are delivered. The best fit will care as much about the quality of the operator and employee experience as the correctness of the backend systems behind it. In this role, you will: - Build frontend experiences that let employees request help, let agents gather context and take safe actions, and let human responders review, approve, or take over without losing the thread. - Reduce reliance on broadly privileged manual actions by replacing them with narrow, auditable, policy-aware automation. - Turn recurring technology support and administration problems into paved-path processes that can be completed consistently and, where appropriate, without a human in the loop. - Build agentic solutions that can understand tickets, gather context, execute safe actions, and escalate intelligently when automation is not enough. - Improve ITSM experiences across intake, routing, execution, handoff, and auditability. - Create reusable tools, APIs, and execution primitives that agents and operators can use safely across enterprise systems. - Design internal applications that pair strong frontend usability with robust backend systems, especially for complex operational tasks. - Partner closely with IT, Security, and business teams to identify where software can remove friction, reduce risk, and improve operational leverage. - Work with IAM and Security partners to ensure internal applications align with Zero Trust principles, RBAC expectations, and compliance needs. - Build backend foundations that support secure products across identity, ITSM, ticketing, and service integrations. - Strengthen monitoring, observability, and incident readiness for the systems behind these experiences. - Manage multiple initiatives while maintaining a high bar for usability, implementation quality, and operational follow-through. You may be right for this role if you have: - Strong experience building production software across both frontend and backend layers, with particular strength in modern frontend development. - Experience designing interfaces for complex operational products, internal tools, or case-management systems. - A track record of turning ambiguous operational problems into clear, usable products or systems. - Solid backend engineering fundamentals in API design, data modeling, integrations, and system reliability. - Experience building internal platforms, support tooling, automation systems, or operational products. - Interest in agentic systems, ITSM, enterprise administration, or software that reduces manual operational burden. - Strong judgment around security, access boundaries, and designing systems that constrain risky actions rather than simply making them easier. - Excellent stakeholder management skills and ability to work cross-functionally with IT, Security, and business teams. - Clear and concise communication skills to explain technical concepts to both technical and non-technical audiences. - A self-starter with strong analytical and problem-solving skills. You might thrive in this role if you have: - Experience with enterprise SaaS administration, identity systems, or privileged operational tooling. - Experience building AI-assisted or agentic support systems. - Experience with ticketing systems, request routing, approval flows, or operational case management. - Experience designing reusable toolsets or platforms consumed by both humans and agents. - Familiarity with compliance frameworks such as SOC 2, ISO 27001, FedRAMP, and NIST. This role is either fully remote or based in San Francisco, CA. We offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.", "summaryDescription" : "Software Engineer, Internal Applications - Enterprise at OpenAI. Skills: Internal applications, Enterprise administration, Agentic systems. Build frontend experiences. Reduce reliance on manual actions", "postedDate" : "2026-06-11T20:32:14.361", "createdAt" : "2026-06-11T20:32:14.361", "lastUpdated" : "2026-06-13T20:19:47.872", "ingestTimestamp" : "2026-06-11T20:32:14.361", "mongoId" : "6a2a7b2274d8ee00a0663552", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 293000, "salaryAnnualMax" : 342000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Automation systems", "Agentic systems", "Internal applications", "Enterprise administration", "Product judgment", "System design", "Operational leverage", "Zero Trust principles", "RBAC expectations", "Compliance needs", "ITSM", "Compliance frameworks", "SOC 2", "ISO 27001", "FedRAMP", "NIST" ], "skillCount" : 16, "jobCategory" : "other", "jobSubcategory" : "security", "dataQualityScore" : 0.8888889, "_score" : 640.88367, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "69c94a889bc74574cbbb5170", "title" : "Data Infrastructure Engineer, Amazon Interactive Video Service (IVS)", "company" : "Amazon Web Services, Inc.", "industry" : "Software Development, Cloud Computing", "salary" : { "min" : 143700.0, "max" : 194400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T01:50:28.091", "fingerprint" : "5d5d45deaadb5eff44edc65f7116fabe64e19be411c16ba7d463446c1614b2af", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3196046/apply", "externalId" : "a87ad0b0-915d-4d6d-9a82-b0741ee84eca", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "AWS, C#, C++, Java, Perl", "professionalSkills" : [ "System design", "Reliability", "Scaling" ], "hardSkillsList" : [ "Data infrastructure", "Data pipelines", "Data quality", "Data reliability", "Data observability", "Performance optimization", "Cost optimization" ], "hardSkills" : [ { "name" : "Data infrastructure", "level" : "intermediate" }, { "name" : "Data pipelines", "level" : "intermediate" }, { "name" : "Data quality", "level" : "intermediate" }, { "name" : "Data reliability", "level" : "intermediate" }, { "name" : "Data observability", "level" : "intermediate" }, { "name" : "Performance optimization", "level" : "intermediate" }, { "name" : "Cost optimization", "level" : "intermediate" } ], "majorSkills" : "Data infrastructure, Data pipelines, AWS", "majorSkillsList" : [ "Data infrastructure", "Data pipelines", "AWS" ], "coreResponsibilities" : "Design scalable data infrastructure in AWS, Implement scalable data infrastructure in AWS, Maintain scalable data infrastructure in AWS, Build data pipelines, Optimize data pipelines, Ensure data quality, Ensure data reliability, Ensure data observability, Work closely with product teams, Work closely with analytics teams, Understand requirements, Deliver high-performance solutions, Champion security best practices, Champion compliance best practices, Champion governance best practices, Identify performance optimization opportunities, Identify cost optimization opportunities, Stay current with emerging tools, Stay current with emerging frameworks, Stay current with emerging cloud services", "teamCollaboration" : "Product teams; Analytics teams; Data Science teams", "domainKnowledge" : "Live streaming; Petabyte-scale data infrastructure; Batch pipelines; Streaming pipelines; Analytics workloads; Reporting workloads; ML workloads; Data products; Data platforms; Cloud services", "domainList" : [ "live-streaming", "petabyte-scale-data-infrastructure", "batch-pipelines", "streaming-pipelines", "analytics-workloads", "reporting-workloads", "ml-workloads", "data-products", "data-platforms", "cloud-services" ], "domainSpecificKnowledge" : [ "Live streaming", "Petabyte-scale data infrastructure", "Batch pipelines", "Streaming pipelines", "Analytics workloads", "Reporting workloads", "ML workloads", "Data products", "Data platforms", "Cloud services" ], "problemSolvingSkills" : "Root cause analysis; Troubleshooting", "qualificationsBasic" : "3+ years software development experience, 2+ years system design/architecture, 1+ years software development engineer experience, 1+ years large-scale distributed software applications, 1+ years Object Oriented Design experience, Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or related field", "qualificationsPreferred" : "3+ years full software development life cycle experience, Bachelor's degree in computer science or equivalent, Experience operating highly available, distributed systems, Experience in software development", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Amazon Interactive Video Service (Amazon IVS) is AWS's fully managed live streaming service, built on the same battle-tested technology that powers Twitch and trusted by thousands of enterprises across gaming, social, live commerce, sports, and entertainment. Our mission: enable developers to build communities around live video. We handle everything from ingest to processing to delivery at global scale, so developers can focus on creating interactive, engaging live experiences for their audiences. Whether you're streaming to tens of millions of concurrent viewers or just getting started, Amazon IVS removes the complexity so developers can move fast. As a Data Infrastructure Engineer, you will be responsible for empowering internal teams and IVS customers with the data they need to make key operational and business decisions. We operate petabyte-scale data infrastructure for collecting, processing, and warehousing IVS data. We support streaming and batch pipelines to facilitate analytics, reporting, and ML workloads. We offer analytics tools and data products designed to make it easy and fast for our customers to extract the insights they need from their data. Key job responsibilities - Design, implement, and maintain scalable data infrastructure in native AWS - Build and optimize data pipelines (batch and streaming) to support analytics, reporting, and ML workloads - Ensure data quality, reliability, and observability through monitoring, logging, and automated alerting - Work closely with product and analytics teams to understand requirements and deliver high-performance solutions - Champion best practices for security, compliance, and governance in data infrastructure - Identify opportunities to optimize performance and cost of data platforms - Stay current with emerging tools, frameworks, and cloud services in the data infrastructure ecosystem A day in the life Your primary focus will be empowering customers to succeed with their data by ensuring they can: - Gather and access data at scale – Enable seamless data collection and retrieval that grows with their needs - Extract meaningful insights – Provide the right tools and capabilities to uncover the answers they're seeking - Trust their data – Maintain confidence in the completeness, accuracy, and reliability of their information Achieving these goals requires close collaboration and strong partnerships with Product and Data Science teams to deliver solutions that truly meet customer needs. Basic Qualifications: - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - 1+ years of software development engineer or related occupational experience - 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience - 1+ years of Object Oriented Design experience - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field - Experience programming with at least one software programming language Preferred Qualifications: - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent - Experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets, or experience in software development Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, San Francisco - 165,200.00 - 223,600.00 USD annually USA, WA, Seattle - 143,700.00 - 194,400.00 USD annually", "summaryDescription" : "Data Infrastructure Engineer, Amazon Interactive Video Service (IVS) at Amazon Web Services, Inc.. Skills: Data infrastructure, Data pipelines, AWS. Design scalable data infrastructure in AWS. Implement scalable data infrastructure in AWS", "postedDate" : "2026-06-13T06:01:37.244", "createdAt" : "2026-06-13T06:01:37.244", "lastUpdated" : "2026-06-15T01:50:28.091", "ingestTimestamp" : "2026-06-13T06:01:37.244", "mongoId" : "69c94a889bc74574cbbb5170", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3196046/apply", "salaryAnnualMin" : 143700, "salaryAnnualMax" : 194400, "salaryBand" : "100k-150k", "hasSalary" : true, "allSkills" : [ "Data infrastructure", "Data pipelines", "Data quality", "Data reliability", "Data observability", "Performance optimization", "Cost optimization", "AWS", "System design", "Reliability", "Scaling", "Live streaming", "Petabyte-scale data infrastructure", "Batch pipelines", "Streaming pipelines", "Analytics workloads", "Reporting workloads", "ML workloads", "Data products", "Data platforms", "Cloud services" ], "skillCount" : 21, "jobCategory" : "engineering", "dataQualityScore" : 0.8888889, "_score" : 639.6602, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "69c94a889bc74574cbbb516d", "title" : "Sr. Data Infrastructure Engineer, Amazon Interactive Video Service (IVS)", "company" : "Amazon Web Services, Inc.", "industry" : "Software Development, Cloud Computing", "salary" : { "min" : 168100.0, "max" : 227400.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Seattle, Washington, USA", "locations" : [ "Seattle, Washington, USA" ], "timestamp" : "2026-06-15T05:40:04.528", "fingerprint" : "99774c7eab44fe19224428fd417cd8e0e0f66576c1f54f1c4db4c4541abbe7b8", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/3196045/apply", "externalId" : "979074d9-b514-4700-a96d-de83cac4416a", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Seattle", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.6038321,-122.3300620" } ], "locationText" : "Seattle, Washington, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AWS, Python, SQL, Spark, Scala, SageMaker, Athena, Redshift, Databricks, Snowflake, BigQuery, dbt, Fivetran, Airflow, Delta Lake, scikit-learn, TensorFlow, PyTorch, XGBoost, LightGBM, Hugging Face, MLflow, S3, Glue, Vertex AI, Synapse, ML Studio", "professionalSkills" : [ "Data engineering", "ML engineering", "Analytics engineering", "Business intelligence", "Quantitative analysis", "System design", "Data warehousing", "Data pipelines", "Data quality", "Data reliability", "Data observability", "Security best practices", "Compliance best practices", "Governance best practices", "Performance optimization", "Cost optimization" ], "hardSkillsList" : [ "Data infrastructure", "Streaming pipelines", "Batch pipelines", "ML workloads", "Automated alerting", "High-performance solutions", "Data infrastructure ecosystem" ], "softSkillsList" : [ "Leadership" ], "hardSkills" : [ { "name" : "Data infrastructure", "level" : "intermediate" }, { "name" : "Streaming pipelines", "level" : "intermediate" }, { "name" : "Batch pipelines", "level" : "intermediate" }, { "name" : "ML workloads", "level" : "intermediate" }, { "name" : "Automated alerting", "level" : "intermediate" }, { "name" : "High-performance solutions", "level" : "intermediate" }, { "name" : "Data infrastructure ecosystem", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Leadership" } ], "majorSkills" : "Data infrastructure, Data pipelines, ML workloads", "majorSkillsList" : [ "Data infrastructure", "Data pipelines", "ML workloads" ], "coreResponsibilities" : "Design scalable data infrastructure, Implement scalable data infrastructure, Maintain scalable data infrastructure, Build data pipelines, Optimize data pipelines, Ensure data quality, Ensure data reliability, Ensure data observability, Work with product teams, Work with analytics teams, Understand requirements, Deliver high-performance solutions, Champion security best practices, Champion compliance best practices, Champion governance best practices, Identify performance optimization opportunities, Identify cost optimization opportunities, Stay current with emerging tools, Stay current with emerging frameworks, Stay current with emerging cloud services", "teamCollaboration" : "Product teams; Analytics teams; Data Science teams", "domainKnowledge" : "Live streaming; Petabyte-scale data infrastructure; Cloud data stacks; Distributed systems", "domainList" : [ "live-streaming", "petabyte-scale-data-infrastructure", "cloud-data-stacks", "distributed-systems" ], "domainSpecificKnowledge" : [ "Live streaming", "Petabyte-scale data infrastructure", "Cloud data stacks", "Distributed systems" ], "toolProficiency" : [ "AWS", "SageMaker", "Athena", "Redshift", "Databricks", "Snowflake", "BigQuery", "dbt", "Fivetran", "Airflow", "Delta Lake", "scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow" ], "problemSolvingSkills" : "Root cause analysis", "qualificationsBasic" : "5+ years software development, 5+ years programming, 5+ years design or architecture, 5+ years software development life cycle, 5+ years operating distributed systems, SQL proficiency, 5+ years experience", "qualificationsPreferred" : "Bachelor's degree in computer science, Experience operating highly available distributed systems, Experience with data extraction, Experience with data ingestion, Experience with data processing, Experience with large data sets", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help. You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. Amazon Interactive Video Service (Amazon IVS) is AWS's fully managed live streaming service, built on the same battle-tested technology that powers Twitch and trusted by thousands of enterprises across gaming, social, live commerce, sports, and entertainment. Our mission: enable developers to build communities around live video. We handle everything from ingest to processing to delivery at global scale, so developers can focus on creating interactive, engaging live experiences for their audiences. Whether you're streaming to tens of millions of concurrent viewers or just getting started, Amazon IVS removes the complexity so developers can move fast. As a Data Infrastructure Engineer, you will be responsible for empowering internal teams and IVS customers with the data they need to make key operational and business decisions. We operate petabyte-scale data infrastructure for collecting, processing, and warehousing IVS data. We support streaming and batch pipelines to facilitate analytics, reporting, and ML workloads. We offer analytics tools and data products designed to make it easy and fast for our customers to extract the insights they need from their data. Key job responsibilities - Design, implement, and maintain scalable data infrastructure in native AWS - Build and optimize data pipelines (batch and streaming) to support analytics, reporting, and ML workloads - Ensure data quality, reliability, and observability through monitoring, logging, and automated alerting - Work closely with product and analytics teams to understand requirements and deliver high-performance solutions - Champion best practices for security, compliance, and governance in data infrastructure - Identify opportunities to optimize performance and cost of data platforms - Stay current with emerging tools, frameworks, and cloud services in the data infrastructure ecosystem A day in the life Your primary focus will be empowering customers to succeed with their data by ensuring they can: - Gather and access data at scale – Enable seamless data collection and retrieval that grows with their needs - Extract meaningful insights – Provide the right tools and capabilities to uncover the answers they're seeking - Trust their data – Maintain confidence in the completeness, accuracy, and reliability of their information Achieving these goals requires close collaboration and strong partnerships with Product and Data Science teams to deliver solutions that truly meet customer needs. Basic Qualifications: - 5+ years of non-internship professional software development experience - 5+ years of programming with at least one software programming language experience - 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience as a mentor, tech lead or leading an engineering team Preferred Qualifications: - 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent - Experience in software development, or experience operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, San Francisco - 193,300.00 - 261,500.00 USD annually USA, WA, Seattle - 168,100.00 - 227,400.00 USD annually", "summaryDescription" : "Sr. Data Infrastructure Engineer, Amazon Interactive Video Service (IVS) at Amazon Web Services, Inc.. Skills: Data infrastructure, Data pipelines, ML workloads. Design scalable data infrastructure. Implement scalable data infrastructure", "postedDate" : "2026-06-13T17:45:30.756", "createdAt" : "2026-06-13T17:45:30.756", "lastUpdated" : "2026-06-15T05:40:04.528", "ingestTimestamp" : "2026-06-13T17:45:30.756", "mongoId" : "69c94a889bc74574cbbb516d", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3196045/apply", "salaryAnnualMin" : 168100, "salaryAnnualMax" : 227400, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Data infrastructure", "Streaming pipelines", "Batch pipelines", "ML workloads", "Automated alerting", "High-performance solutions", "Data infrastructure ecosystem", "Leadership", "Data pipelines", "Data engineering", "ML engineering", "Analytics engineering", "Business intelligence", "Quantitative analysis", "System design", "Data warehousing", "Data quality", "Data reliability", "Data observability", "Security best practices", "Compliance best practices", "Governance best practices", "Performance optimization", "Cost optimization", "Live streaming", "Petabyte-scale data infrastructure", "Cloud data stacks", "Distributed systems", "AWS", "SageMaker", "Athena", "Redshift", "Databricks", "Snowflake", "BigQuery", "dbt", "Fivetran", "Airflow", "Delta Lake", "scikit-learn", "TensorFlow", "PyTorch", "XGBoost", "LightGBM", "Hugging Face", "MLflow" ], "skillCount" : 46, "jobCategory" : "engineering", "dataQualityScore" : 1.0, "_score" : 636.9068, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a3050abf292fd229cef38ef", "title" : "Enterprise Account Executive", "company" : "Kong Inc.", "industry" : "All Cost Center", "salary" : { "min" : 200000.0, "max" : 350000.0, "currency" : "SGD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Enterprise Account Executive in Singapore, adjusted for executive seniority and technology industry." }, "location" : "Singapore", "locations" : [ "Singapore" ], "timestamp" : "2026-06-16T10:29:25.759", "fingerprint" : "f6d139f43d79143dfa568b375691b21d5ab0ad1a31b1755d04cbd944cc5825dc", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/kong/8b22e1b8-9238-4c95-a697-122011c4f238/application", "externalId" : "8b22e1b8-9238-4c95-a697-122011c4f238", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Singapore", "country" : "Singapore", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "1.2899175,103.8519072" } ], "locationText" : "Singapore, Singapore", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "professionalSkills" : [ "Account planning", "Forecasting", "Pipeline generation" ], "hardSkillsList" : [ "Sales techniques", "Negotiation", "Presentation", "Closing skills" ], "hardSkills" : [ { "name" : "Sales techniques", "level" : "intermediate" }, { "name" : "Negotiation", "level" : "intermediate" }, { "name" : "Presentation", "level" : "intermediate" }, { "name" : "Closing skills", "level" : "intermediate" } ], "majorSkills" : "Enterprise software sales, Account management, Pipeline development", "majorSkillsList" : [ "Enterprise software sales", "Account management", "Pipeline development" ], "coreResponsibilities" : "Sell Kong Enterprise Platform, Develop pipeline generation strategy, Execute pipeline generation strategy, Meet individual quotas, Meet individual objectives, Manage assigned territory account planning, Manage assigned territory forecasting, Take ownership of book of business, Document buying criteria, Document buying process, Determine appropriate sales motions, Determine appropriate sales patterns, Ensure pipeline accuracy based on evidence, Work leads to closure, Represent Kong professionally, Support customers", "teamCollaboration" : "Collaborate with internal teams; Collaborate with product; Collaborate with marketing; Collaborate with customer success", "domainKnowledge" : "API connectivity; AI connectivity", "domainList" : [ "api-connectivity", "ai-connectivity" ], "domainSpecificKnowledge" : [ "API connectivity", "AI connectivity" ], "communicationSkills" : "Effective communicator; Interpersonal skills; Presentation skills", "problemSolvingSkills" : "Analytical thinking; Strategic thinking", "specialRequirements" : "Ability to travel to customer sites", "qualificationsBasic" : "10 years or more of experience in selling enterprise software, Network in the enterprise domain, Demonstrated success in selling to assigned named accounts, Demonstrated success selling to senior-level executives, Demonstrated success selling across multiple departments", "qualificationsPreferred" : "Open source experience, Experience selling early-stage enterprise software products", "remoteFriendly" : false, "workSiteFlexibility" : "Flexible", "rawDescription" : "Are you ready to unlock intelligence? If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others. About the role: We are looking for an experienced sales professional, ideally with open source experience, who will be selling into enterprise accounts. The ideal candidate has been a part of the sales efforts for other early-stage enterprise software products in an entrepreneurial setting. The Enterprise Account Executive will be integral to our growth plan and in acquiring new customers. Kong’s Account Executive will be the primary point of contact and the face of Kong for our prospects. What You’ll Be Doing: - Sell Kong Enterprise Platform to enterprise customers by developing and executing a pipeline generation strategy that will create a viable and long-term business. - Meet individual quotas and objectives. - Responsible for assigned territory account planning and forecasting. - Take ownership of your book of business, which includes understanding and documenting the buying criteria and process, determining the appropriate motions and patterns, ensuring pipeline accuracy based on evidence, and working the leads to closure. - Collaborate with internal teams, including product, marketing, and customer success, to ensure a seamless sales experience and alignment with customer needs. - Represent Kong most professionally and support our customers to the best of your ability. - Ability to travel to customer sites as required. What You’ll Bring: - A true desire to see customers benefit from the investment they make with Kong. - 10 years or more of experience in selling enterprise software with a strong network in the enterprise domain. - Demonstrated success in selling to assigned named accounts, particularly to senior-level executives and across multiple departments. - Ability to leverage established relationships and proven sales techniques for success. - Ability to thrive in a fast-paced, entrepreneurial environment, taking ownership of your sales territory and adapting to changing market dynamics. - Analytical and strategic thinking, with a knack for identifying business growth opportunities and devising plans to capitalise on them. - Effective communicator and strong interpersonal skills. - Excellent negotiation, presentation, and closing skills. - Motivated, driven and results-oriented. #LI-SP1 About Kong: Kong Inc., a leading developer of API and AI connectivity technologies, is building the infrastructure that powers the agentic era. Trusted by the Fortune 500 and startups alike, Kong's unified API and AI platform, Kong Konnect, enables organizations to secure, manage, accelerate, govern, and monetize the flow of intelligence across APIs and AI models. For more information, visit www.konghq.com http://www.konghq.com.", "summaryDescription" : "Enterprise Account Executive at Kong Inc.. Skills: Enterprise software sales, Account management, Pipeline development. Sell Kong Enterprise Platform. Develop pipeline generation strategy", "createdAt" : "2026-06-16T00:30:31.254", "lastUpdated" : "2026-06-16T10:29:25.759", "ingestTimestamp" : "2026-06-16T00:30:31.254", "mongoId" : "6a3050abf292fd229cef38ef", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Sales techniques", "Negotiation", "Presentation", "Closing skills", "Enterprise software sales", "Account management", "Pipeline development", "Account planning", "Forecasting", "Pipeline generation", "API connectivity", "AI connectivity" ], "skillCount" : 12, "jobCategory" : "sales", "jobSubcategory" : "revenue", "seniorityLevel" : "Executive", "dataQualityScore" : 0.8888889, "_score" : 636.32007, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.98 }, { "id" : "6a2ca8e674d8ee00a09c4d25", "title" : "IT Infrastructure & Cloud Engineer", "company" : "OMNI", "industry" : "Federal DoD", "salary" : { "min" : 95000.0, "max" : 135000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for IT Infrastructure & Cloud Engineer in Chantilly, United States, adjusted for mid-level seniority and technology industry." }, "location" : "Chantilly, VA, Virginia, United States", "locations" : [ "Chantilly, VA, Virginia, United States" ], "timestamp" : "2026-06-16T01:22:52.411", "fingerprint" : "3c18bf3b4899c5590a409cb7cb09bd4296a95a879d98cbd1e91c92ae465989b0", "source" : "recruitee", "language" : "en", "applyUrl" : "https://omniconsultcorp.recruitee.com/o/it-infrastructure-cloud-engineer/c/new", "externalId" : "2639192", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Chantilly", "state" : "Virginia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "38.8852190,-77.4486772" } ], "locationText" : "Chantilly, Virginia, United States", "employmentType" : "FULL_TIME", "minimumEducation" : "bachelor's degree", "experienceMinYears" : 5, "experienceLevel" : "experienced", "technicalSkills" : "AWS, Microsoft Azure, Google Cloud Platform, Enterprise networking, Virtualization technologies, Server infrastructure, Storage solutions", "professionalSkills" : [ "Technical leadership", "Government oversight", "Project execution", "Risk assessment", "Issue resolution" ], "hardSkillsList" : [ "Infrastructure deployment", "Cloud modernization", "IT equipment integration", "Service acceptance", "Site assessment" ], "hardSkills" : [ { "name" : "Infrastructure deployment", "level" : "intermediate" }, { "name" : "Cloud modernization", "level" : "intermediate" }, { "name" : "IT equipment integration", "level" : "intermediate" }, { "name" : "Service acceptance", "level" : "intermediate" }, { "name" : "Site assessment", "level" : "intermediate" } ], "majorSkills" : "Cloud modernization, Enterprise infrastructure, Government oversight", "majorSkillsList" : [ "Cloud modernization", "Enterprise infrastructure", "Government oversight" ], "coreResponsibilities" : "Provide Government oversight for deployments, upgrades, and modernization, Coordinate installation, integration, testing, and acceptance of IT, Coordinate integration of cloud-enabled services, Serve as liaison between Government and contractor teams, Support facility stand-up, expansion, and operational transition, Evaluate cloud migration strategies, Evaluate infrastructure modernization initiatives, Conduct site visits to assess infrastructure readiness, Conduct site visits to assess operational capabilities, Conduct site visits to assess deployment progress, Develop technical briefings, Develop status reports, Develop risk assessments, Develop recommendations for leadership, Monitor project schedules, Identify project risks, Provide recommendations to support mission success, Collaborate with cross-functional teams, Ensure infrastructure solutions align with requirements, Ensure infrastructure solutions align with security standards", "teamCollaboration" : "Government stakeholders; Contractor teams; Cross-functional teams", "projectManagementSkills" : [ "Project schedules", "Risk assessment" ], "domainKnowledge" : "National security missions; Enterprise environments", "domainList" : [ "national-security-missions", "enterprise-environments" ], "domainSpecificKnowledge" : [ "National security missions", "Enterprise environments" ], "communicationSkills" : "Brief senior leadership; Technical briefings; Status reports", "documentationSkills" : "Technical writing", "problemSolvingSkills" : "Issue resolution; Risk assessment", "specialRequirements" : "CONUS travel required, Active TS/SCI Polygraph preferred, U. S. Citizenship required", "outcomesObjectives" : "Ensure successful implementation of infrastructure solutions; Support mission success", "qualificationsBasic" : "Bachelor's degree in IT, Computer Science, Systems Engineering, or related, 5+ years supporting enterprise infrastructure, cloud, or IT modernization, Experience with AWS, Azure, or GCP, Knowledge of enterprise networking, virtualization, server, and storage, Experience coordinating infrastructure deployments across multiple sites, Analytical, organizational, and communication skills, Active TS/SCI clearance required, U. S. Citizenship required", "qualificationsPreferred" : "Polygraph preferred", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Position Title: IT Infrastructure & Cloud Engineer Location: Chantilly, VA Clearance: Active TS/SCI required; Polygraph preferred U.S. Citizenship required Travel: CONUS travel required #### Position Overview OMNI is seeking an experienced IT Infrastructure & Cloud Engineer to provide technical leadership and Government oversight supporting enterprise infrastructure deployments, cloud modernization initiatives, and facility stand-up activities. This role will work closely with Government stakeholders and contractor teams to ensure successful implementation of infrastructure solutions that support critical national security missions. #### Key Responsibilities * Provide Government oversight for enterprise infrastructure deployments, upgrades, and modernization efforts. * Coordinate the installation, integration, testing, and acceptance of IT equipment and cloud-enabled services. * Serve as the primary liaison between Government stakeholders and contractor teams to support project execution and issue resolution. * Support facility stand-up, expansion, and operational transition activities. * Evaluate cloud migration strategies and infrastructure modernization initiatives across enterprise environments. * Conduct site visits to assess infrastructure readiness, operational capabilities, and deployment progress. * Develop technical briefings, status reports, risk assessments, and recommendations for Government leadership. * Monitor project schedules, identify risks, and provide recommendations to support mission success. * Collaborate with cross-functional teams to ensure infrastructure solutions align with operational requirements and security standards. ## Requirements 1. Bachelor's degree in Information Technology, Computer Science, Systems Engineering, or a related technical field. 2. Minimum of 5 years of experience supporting enterprise infrastructure, cloud environments, or IT modernization initiatives. 3. Experience with one or more cloud platforms, including AWS, Microsoft Azure, or Google Cloud Platform (GCP). 4. Knowledge of enterprise networking, virtualization technologies, server infrastructure, and storage solutions. 5. Experience coordinating infrastructure deployments across multiple sites and stakeholder organizations. 6. Strong analytical, organizational, and communication skills with the ability to brief senior leadership. 7. Active TS/SCI clearance required ; Polygraph preferred. 8. U.S. Citizenship required. Why Join OMNI? OMNI Consulting Solutions is a boutique consulting firm specializing in creating game-changing value and simple solutions for complex demands. OMNI is built on the idea that change moves the world forward, and through creative and entrepreneurial leadership OMNI maintains a bold reputation within the DoD/Aerospace community and across the various other industries we support. As an OMNI employee, you can be assured of extensive growth opportunities, inordinately competitive salary compensation packages, and the unparalleled support of the OMNI family. We are an equal-opportunity employer, and our benefits packages are designed to meet the needs of all our employees and dependents: * Medical Coverage * Dental Benefits * Vision Benefits * Life Insurance * 401(k) Retirement Plan with Employer Matching * Fully Vested on Day 1 of Employment * Paid Time Off & Sick Leave * Company Sponsored Social Events IS IT A MATCH? If you are interested in this position or other opportunities at OMNI, please let us know! We only need your resume and some basic details to get things started. Even if you aren't a match, we may still be interested! We will keep your resume on-file and will let you know if something matching your skills comes along. Job Code (6.26.6)", "summaryDescription" : "IT Infrastructure & Cloud Engineer at OMNI. Skills: Cloud modernization, Enterprise infrastructure, Government oversight. Provide Government oversight for deployments, upgrades, and modernization. Coordinate installation, integration, testing, and acceptance of IT", "postedDate" : "2026-06-12T16:16:37.000", "createdAt" : "2026-06-14T19:46:52.137", "lastUpdated" : "2026-06-16T01:22:52.411", "ingestTimestamp" : "2026-06-14T19:46:52.137", "mongoId" : "6a2ca8e674d8ee00a09c4d25", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 95000, "salaryAnnualMax" : 135000, "salaryBand" : "75k-100k", "hasSalary" : true, "allSkills" : [ "Infrastructure deployment", "Cloud modernization", "IT equipment integration", "Service acceptance", "Site assessment", "Enterprise infrastructure", "Government oversight", "Technical leadership", "Project execution", "Risk assessment", "Issue resolution", "Project schedules", "National security missions", "Enterprise environments" ], "skillCount" : 14, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 1.0, "_score" : 635.2732, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a3050abf292fd229cef38ee", "title" : "Enterprise Account Manager", "company" : "Kong Inc.", "industry" : "All Cost Center", "salary" : { "min" : 2500000.0, "max" : 4000000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Enterprise Account Manager in India, adjusted for Seniority, Technology industry, and Mumbai/Pune city tier." }, "location" : "India-Maharashtra", "locations" : [ "India-Maharashtra" ], "timestamp" : "2026-06-16T08:55:21.786", "fingerprint" : "84d8212a34fb0323899f090009f799114f1d04db4efe7501c06235d42bd5ea03", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/kong/0322932b-a817-4d25-b784-ea23316852ef/application", "externalId" : "0322932b-a817-4d25-b784-ea23316852ef", "industryFunction" : { }, "structuredLocations" : [ { "state" : "Maharashtra", "country" : "India", "continent" : "as", "workMode" : "onsite" } ], "locationText" : "Maharashtra, India", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "professionalSkills" : [ "Pipeline generation", "Account planning", "Forecasting", "Sales techniques", "Business growth" ], "hardSkillsList" : [ "Enterprise software sales" ], "hardSkills" : [ { "name" : "Enterprise software sales", "level" : "intermediate" } ], "majorSkills" : "Enterprise account management, Sales pipeline management, Customer acquisition", "majorSkillsList" : [ "Enterprise account management", "Sales pipeline management", "Customer acquisition" ], "coreResponsibilities" : "Sell Kong Enterprise Platform, Develop pipeline generation strategy, Execute pipeline generation strategy, Create long-term business, Meet individual quotas, Meet individual objectives, Plan assigned territory accounts, Forecast assigned territory accounts, Own book of business, Document buying criteria, Document buying process, Determine appropriate sales motions, Determine appropriate sales patterns, Ensure pipeline accuracy, Work leads to closure, Collaborate with internal teams, Ensure seamless sales experience, Align with customer needs, Represent Kong professionally, Support customers", "teamCollaboration" : "Collaborate with product; Collaborate with marketing; Collaborate with customer success", "domainKnowledge" : "API connectivity; AI connectivity", "domainList" : [ "api-connectivity", "ai-connectivity" ], "domainSpecificKnowledge" : [ "API connectivity", "AI connectivity" ], "communicationSkills" : "Interpersonal skills; Negotiation skills; Presentation skills; Closing skills", "problemSolvingSkills" : "Analytical thinking; Strategic thinking", "specialRequirements" : "30% - 50% travel", "outcomesObjectives" : "Acquire new customers; Achieve individual quotas; Achieve individual objectives", "qualificationsBasic" : "7 years or more of experience in selling enterprise software, Demonstrated success in selling to large enterprises, Ability to thrive in a fast-paced, entrepreneurial environment, Analytical and strategic thinking, Effective communicator and interpersonal skills, Excellent negotiation, presentation, and closing skills", "qualificationsPreferred" : "Open source experience, Experience selling early-stage enterprise software products", "remoteFriendly" : true, "rawDescription" : "Are you ready to unlock intelligence? If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others. About the role: We are looking for an experienced sales professional, ideally with open source experience, who will be selling into enterprise accounts. The ideal candidate has been a part of the sales efforts for other early-stage enterprise software products in an entrepreneurial setting. The Enterprise Account Executive will be integral to our growth plan and in acquiring new customers. Kong’s Account Executive will be the primary point of contact and the face of Kong for our prospects. What You’ll Be Doing: - Sell Kong Enterprise Platform to enterprise customers by developing and executing a pipeline generation strategy that will create a viable and long-term business. - Meet individual quotas and objectives. - Responsible for assigned territory account planning and forecasting. - Take ownership of your book of business, which includes understanding and documenting the buying criteria and process, determining the appropriate motions and patterns, ensuring pipeline accuracy based on evidence, and working the leads to closure. - Collaborate with internal teams, including product, marketing, and customer success, to ensure a seamless sales experience and alignment with customer needs. - Represent Kong most professionally and support our customers to the best of your ability. - Ability to travel to customer sites as required (30% - 50%). What You’ll Bring: - A true desire to see customers benefit from the investment they make with Kong. - 7 years or more of experience in selling enterprise software. - Demonstrated success in selling to large enterprises, particularly to senior-level executives and across multiple departments. - Ability to leverage established relationships and proven sales techniques for success. - Ability to thrive in a fast-paced, entrepreneurial environment, taking ownership of your sales territory and adapting to changing market dynamics. - Analytical and strategic thinking, with a knack for identifying business growth opportunities and devising plans to capitalise on them. - Effective communicator and strong interpersonal skills. - Excellent negotiation, presentation, and closing skills. - Motivated, driven and results-oriented. #LI-SP1 About Kong: Kong Inc., a leading developer of API and AI connectivity technologies, is building the infrastructure that powers the agentic era. Trusted by the Fortune 500 and startups alike, Kong's unified API and AI platform, Kong Konnect, enables organizations to secure, manage, accelerate, govern, and monetize the flow of intelligence across APIs and AI models. For more information, visit www.konghq.com http://www.konghq.com.", "summaryDescription" : "Enterprise Account Manager at Kong Inc.. Skills: Enterprise account management, Sales pipeline management, Customer acquisition. Sell Kong Enterprise Platform. Develop pipeline generation strategy", "createdAt" : "2026-06-16T00:31:09.412", "lastUpdated" : "2026-06-16T08:55:21.786", "ingestTimestamp" : "2026-06-16T00:31:09.412", "mongoId" : "6a3050abf292fd229cef38ee", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Enterprise software sales", "Enterprise account management", "Sales pipeline management", "Customer acquisition", "Pipeline generation", "Account planning", "Forecasting", "Sales techniques", "Business growth", "API connectivity", "AI connectivity" ], "skillCount" : 11, "jobCategory" : "sales", "jobSubcategory" : "revenue", "seniorityLevel" : "Senior", "dataQualityScore" : 0.8888889, "_score" : 634.39246, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.97 }, { "id" : "6a2a714f74d8ee00a0648ec2", "title" : "Software Engineer, Internal Applications - Enterprise", "company" : "OpenAI", "industry" : "Security", "salary" : { "min" : 293000.0, "max" : 342000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-12T22:58:59.874", "fingerprint" : "3816765eadc9209fc6693b02c20842917102cf1b47c71a44dc378b18b9e16c72", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/openai/db053b0e-c1a5-4b7a-bcb6-6e766629e7b1/application", "externalId" : "db053b0e-c1a5-4b7a-bcb6-6e766629e7b1", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "Frontend development, Backend engineering, API design, Data modeling, System reliability, IAM, ITSM", "professionalSkills" : [ "Product judgment", "System design", "Operational leverage", "Zero Trust principles", "RBAC expectations", "Compliance needs" ], "hardSkillsList" : [ "Automation systems", "Agentic systems" ], "hardSkills" : [ { "name" : "Automation systems", "level" : "intermediate" }, { "name" : "Agentic systems", "level" : "intermediate" } ], "majorSkills" : "Internal applications, Enterprise systems, Agentic systems", "majorSkillsList" : [ "Internal applications", "Enterprise systems", "Agentic systems" ], "coreResponsibilities" : "Build frontend experiences, Reduce reliance on manual actions, Turn problems into paved paths, Build agentic solutions, Improve ITSM experiences, Create reusable tools, Design internal applications, Partner with IT teams, Partner with Security teams, Partner with business teams, Work with IAM partners, Work with Security partners, Build backend foundations, Strengthen monitoring, Strengthen observability, Strengthen incident readiness, Manage multiple initiatives", "teamCollaboration" : "Cross-functionally with IT; Cross-functionally with Security; Cross-functionally with business teams", "domainKnowledge" : "Enterprise administration; AI-assisted support; Ticketing systems; Request routing; Approval flows; Case management; Compliance frameworks; SOC 2; ISO 27001; FedRAMP; NIST; Identity systems; Privileged tooling; Zero Trust principles; RBAC", "domainList" : [ "enterprise-administration", "ai-assisted-support", "ticketing-systems", "request-routing", "approval-flows", "case-management", "compliance-frameworks", "soc-2", "iso-27001", "fedramp", "nist", "identity-systems", "privileged-tooling", "zero-trust-principles", "rbac" ], "domainSpecificKnowledge" : [ "Enterprise administration", "AI-assisted support", "Ticketing systems", "Request routing", "Approval flows", "Case management", "Compliance frameworks", "SOC 2", "ISO 27001", "FedRAMP", "NIST", "Identity systems", "Privileged tooling", "Zero Trust principles", "RBAC" ], "communicationSkills" : "Explain technical concepts", "problemSolvingSkills" : "Problem-solving skills", "qualificationsBasic" : "Experience building production software, Experience designing interfaces for complex operational products, Track record of turning ambiguous operational problems into clear products, Solid backend engineering fundamentals, Experience building internal platforms, Judgment around security and access boundaries, Excellent stakeholder management skills, Clear and concise communication skills, Analytical and problem-solving skills", "qualificationsPreferred" : "Enterprise SaaS administration experience, Identity systems experience, Privileged operational tooling experience, Building AI-assisted support systems experience, Ticketing systems experience, Request routing experience, Approval flows experience, Operational case management experience, Designing reusable toolsets experience, Familiarity with compliance frameworks", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "About the Team OpenAI’s Platform and Infrastructure Engineering organization advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient technology solutions. Our team builds and maintains robust infrastructure that safeguards OpenAI’s data and systems while ensuring employees are well-equipped and seamlessly connected. By prioritizing security, reliability, and user-centric solutions, we empower OpenAI employees to drive impactful AI research, corporate operations, and product innovation. About the Role As a Software Engineer: Internal Applications, Enterprise, you will build internal products that make technology support and administration safer, faster, and less dependent on manual intervention. You will help reduce reliance on broadly privileged human actions, turn recurring technology problems into paved paths, and build agentic systems that can help resolve tickets end to end. A core part of the role is building the interfaces that bring employees, AI agents, and human responders together in a shared ITSM experience, with the right context, controls, and handoffs at each step. We are seeking engineers who enjoy working across frontend and backend layers on ambiguous, high-leverage enterprise problems. You should bring strong product judgment, solid backend engineering fundamentals, and an interest in building software that changes how technology support, system administration, and agent-assisted operations are delivered. The best fit will care as much about the quality of the operator and employee experience as the correctness of the backend systems behind it. In this role, you will: - Build frontend experiences that let employees request help, let agents gather context and take safe actions, and let human responders review, approve, or take over without losing the thread. - Reduce reliance on broadly privileged manual actions by replacing them with narrow, auditable, policy-aware automation. - Turn recurring technology support and administration problems into paved-path processes that can be completed consistently and, where appropriate, without a human in the loop. - Build agentic solutions that can understand tickets, gather context, execute safe actions, and escalate intelligently when automation is not enough. - Improve ITSM experiences across intake, routing, execution, handoff, and auditability. - Create reusable tools, APIs, and execution primitives that agents and operators can use safely across enterprise systems. - Design internal applications that pair strong frontend usability with robust backend systems, especially for complex operational tasks. - Partner closely with IT, Security, and business teams to identify where software can remove friction, reduce risk, and improve operational leverage. - Work with IAM and Security partners to ensure internal applications align with Zero Trust principles, RBAC expectations, and compliance needs. - Build backend foundations that support secure products across identity, ITSM, ticketing, and service integrations. - Strengthen monitoring, observability, and incident readiness for the systems behind these experiences. - Manage multiple initiatives while maintaining a high bar for usability, implementation quality, and operational follow-through. You may be right for this role if you have: - Strong experience building production software across both frontend and backend layers, with particular strength in modern frontend development. - Experience designing interfaces for complex operational products, internal tools, or case-management systems. - A track record of turning ambiguous operational problems into clear, usable products or systems. - Solid backend engineering fundamentals in API design, data modeling, integrations, and system reliability. - Experience building internal platforms, support tooling, automation systems, or operational products. - Interest in agentic systems, ITSM, enterprise administration, or software that reduces manual operational burden. - Strong judgment around security, access boundaries, and designing systems that constrain risky actions rather than simply making them easier. - Excellent stakeholder management skills and ability to work cross-functionally with IT, Security, and business teams. - Clear and concise communication skills to explain technical concepts to both technical and non-technical audiences. - A self-starter with strong analytical and problem-solving skills. You might thrive in this role if you have: - Experience with enterprise SaaS administration, identity systems, or privileged operational tooling. - Experience building AI-assisted or agentic support systems. - Experience with ticketing systems, request routing, approval flows, or operational case management. - Experience designing reusable toolsets or platforms consumed by both humans and agents. - Familiarity with compliance frameworks such as SOC 2, ISO 27001, FedRAMP, and NIST. This role is either fully remote or based in San Francisco, CA. We offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.", "summaryDescription" : "Software Engineer, Internal Applications - Enterprise at OpenAI. Skills: Internal applications, Enterprise systems, Agentic systems. Build frontend experiences. Reduce reliance on manual actions", "postedDate" : "2026-06-11T17:41:42.601", "createdAt" : "2026-06-11T17:41:42.601", "lastUpdated" : "2026-06-12T22:58:59.874", "ingestTimestamp" : "2026-06-11T17:41:42.601", "mongoId" : "6a2a714f74d8ee00a0648ec2", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 293000, "salaryAnnualMax" : 342000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Automation systems", "Agentic systems", "Internal applications", "Enterprise systems", "Product judgment", "System design", "Operational leverage", "Zero Trust principles", "RBAC expectations", "Compliance needs", "Enterprise administration", "AI-assisted support", "Ticketing systems", "Request routing", "Approval flows", "Case management", "Compliance frameworks", "SOC 2", "ISO 27001", "FedRAMP", "NIST", "Identity systems", "Privileged tooling", "RBAC" ], "skillCount" : 24, "jobCategory" : "other", "jobSubcategory" : "security", "dataQualityScore" : 0.8888889, "_score" : 634.3768, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2c6cb474d8ee00a091abe8", "title" : "Agentic Mobile Engineer", "company" : "TransferGo", "industry" : "FinTech", "salary" : { "min" : 100000.0, "max" : 150000.0, "currency" : "PLN", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market data for a Junior Agentic Mobile Engineer in Krakow, Poland, adjusted for mid-level experience and the FinTech industry." }, "location" : "Kraków, Poland", "locations" : [ "Kraków", "Poland", "Vilnius", "Lithuania", "Warsaw", "Poland" ], "timestamp" : "2026-06-15T09:27:46.164", "fingerprint" : "85943ec2f18b7ac82ebe7212944cadfd61658fbc9e02593b3ee9522d19620be2", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://job-boards.greenhouse.io/transfergo/jobs/6021760004", "externalId" : "6021760004", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Kraków", "country" : "Poland", "continent" : "eu", "source" : "llm", "workMode" : "hybrid", "geo" : "50.0469432,19.9971534" } ], "locationText" : "Kraków, Poland", "employmentType" : "FULL_TIME", "experienceMinYears" : 2, "experienceMaxYears" : 5, "experienceLevel" : "Mid", "technicalSkills" : "Swift, SwiftUI, UIKit, Kotlin, Android, TypeScript, React, SOLID, Combine, RxSwift", "professionalSkills" : [ "Product mindset", "Engineering fundamentals", "Agentic AI" ], "hardSkillsList" : [ "IOS development", "Mobile development", "Cross-platform development", "Reactive programming", "Unit testing", "Dependency injection", "Code review" ], "softSkillsList" : [ "Continuous learning", "Teamwork" ], "hardSkills" : [ { "name" : "IOS development", "level" : "intermediate" }, { "name" : "Mobile development", "level" : "intermediate" }, { "name" : "Cross-platform development", "level" : "intermediate" }, { "name" : "Reactive programming", "level" : "intermediate" }, { "name" : "Unit testing", "level" : "intermediate" }, { "name" : "Dependency injection", "level" : "intermediate" }, { "name" : "Code review", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Continuous learning" }, { "name" : "Teamwork" } ], "majorSkills" : "Agentic AI, IOS Development, SwiftUI", "majorSkillsList" : [ "Agentic AI", "IOS Development", "SwiftUI" ], "coreResponsibilities" : "Drive development of solutions, Maintain platform integrity, Diagnose regression issues, Fix regression issues, Play role in release workflows, Engage in incident response, Engage in planning sessions, Engage in retrospectives, Engage in daily standups, Elevate application quality, Elevate application performance, Leverage industry advancements, Deliver user journeys", "teamCollaboration" : "Collaborate with teammates; Collaborate with departments; Collaborative team rituals", "projectManagementSkills" : [ "Planning sessions", "Retrospectives", "Daily standups" ], "domainKnowledge" : "Fintech; Booking flow; Recipients; Pricing; Payments; Core banking; Spend; Compliance", "domainList" : [ "fintech", "booking-flow", "recipients", "pricing", "payments", "core-banking", "spend", "compliance" ], "domainSpecificKnowledge" : [ "Fintech", "Booking flow", "Recipients", "Pricing", "Payments", "Core banking", "Spend", "Compliance" ], "toolProficiency" : [ "Claude Code", "Cursor", "Codex" ], "continuousLearning" : "Annual Development Budget", "innovationCreativity" : "Leverage cutting-edge advancements; Deliver modern journeys; Deliver creative journeys; Deliver compelling journeys", "problemSolvingSkills" : "Diagnose issues; Fix issues; Find ways to elevate quality; Find ways to elevate performance", "outcomesObjectives" : "Impact user conversion; Impact user retention", "qualificationsBasic" : "2+ years shipping iOS, 2+ years Swift, 2+ years SwiftUI, Hands-on agentic coding tool, SOLID principles, Architectural patterns, Reactive concepts, Unit testing, Dependency injection, Critical code reviews", "qualificationsPreferred" : "UIKit a plus, Desire to work cross platforms, Kotlin/Android stack, TypeScript + React/web stack, Backend language stack, Modular architecture, Shipped in 2+ platforms, Reviews code daily, Writes effective agent specs, Autonomous and collaborative, Appetite for learning, Enjoys teamwork, Self-starting initiative", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "TransferGo is a growing fintech scale-up on a mission to champion financial freedom with care. We strive to provide tailored, more affordable financial services that make people's hard-earned money go further. Now in our 14th year, with close to 400 employees in offices across Europe and the UK, we’re crafting a brilliant, relevant product that makes a difference in people's lives and the well-being of their families. We’ve come this far by building a talented, diverse workforce on a fair culture and our strong values. Having this strong team of employees, we can serve those who really need our product to make their lives better. Your team & impact By joining the Engage team, you will contribute to the most critical user journey within our business. This role offers significant technical depth and exposure across various domains, providing you with end-to-end ownership and a clear view of how your work impacts user conversion and retention. Our team manages the booking flow for both SME and Private users, covering domains such as recipients, pricing, and booking. In this position, you will collaborate closely with your direct teammates and various cross-functional departments, including Payments, Core Banking, Spend, Compliance, and Design. Here’s what you’ll be doing as Agentic Mobile Engineer: Drive the development of comprehensive, cross-platform solutions for the booking domain. Maintain platform integrity by diagnosing and fixing regression issues. Play an active role in release workflows and incident response efforts. Engage in collaborative team rituals, including planning sessions, retrospectives, and daily standups. Proactively find ways to elevate the overall quality and performance of the application. Leverage cutting-edge industry advancements to deliver modern, creative, and compelling user journeys. Here’s what we’d love from our new Agentic Mobile Engineer: We don’t expect you to meet every single requirement listed. What matters most is your motivation, mindset, and ability to learn. If you’re excited about this role and think you could be a great fit, we’d really like to hear from you. Strong product mindset: focus on problems, outcomes, and impact—not just tickets or tasks Daily, hands-on agentic AI - genuinely drives work through an agent (Cursor / Claude Code / Codex), not occasional autocomplete. 2+ years shipping production iOS in Swift + SwiftUI (UIKit a plus) Engineering fundamentals they can apply, not recite Desire to work cross platforms At least one agentic coding tool, hands-on: Claude Code, Cursor or similar Core engineering: SOLID, architectural patterns, reactive concepts (Combine or RxSwift), Unit testing, Dependency injection Reviews code critically (catches retain cycles, over-engineering, bugs in AI output) And if you can also do this stuff, even better: A second stack: Kotlin/Android, TypeScript + React/web, or a backend language Modular architecture Already shipped in 2+ platforms Reviews code in languages they don't write daily Writes effective agent specs / skills / rules / guardrails Capable of performing both autonomously and as a collaborative team member Possesses a strong appetite for continuous learning and professional growth Enjoys and actively seeks out opportunities for teamwork Demonstrates strong self-starting initiative What We Offer: Competitive Salary: Starting from €3,100 - €4,660 (gross) per month, depending on experience. Salary is just one part of the conversation – if you’re excited about the role but the range feels slightly off, don’t hesitate to apply. We’re open to discussing based on your experience and potential. Comprehensive Benefits: Including a generous holiday allowance, competitive healthcare insurance, and a wellbeing package from day one. Annual Development Budget: €1,000 to invest in your personal and professional growth. Hybrid Working Environment: Flexibility to work from home and in the office, with most team members in the office two days a week. Pet-Friendly Office: If you’re near one of our offices, bring your furry friend along! Inclusive Culture: Regular in-person events, fostering a strong sense of community and collaboration. At TransferGo, we are committed to the equal treatment of all current and prospective employees. We will not tolerate discrimination on the basis of age, disability, sex, sexual orientation, pregnancy and maternity, race or ethnicity, religion or belief, gender identity, marriage, civil partnership or any other protected category. We are proud of our diverse and inclusive culture and we strongly encourage suitably qualified applicants from a wide range of backgrounds to apply and join TransferGo. We look forward to meeting you! Please note that all data collected will be handled in accordance with our candidates privacy policy (https://www.transfergo.com/privacy-policy/overview) and will only be used for the purpose of evaluating your candidacy. The data will be securely stored and deleted according to retention timeframe set in the candidates privacy policy. If you have any questions or concerns regarding this, please feel free to reach out by replying or via dpo@transfergo.com", "summaryDescription" : "Agentic Mobile Engineer at TransferGo. Skills: Agentic AI, IOS Development, SwiftUI. Drive development of solutions. Maintain platform integrity", "postedDate" : "2026-06-14T08:07:46.081", "createdAt" : "2026-06-14T08:07:46.081", "lastUpdated" : "2026-06-15T09:27:46.164", "ingestTimestamp" : "2026-06-14T08:07:46.081", "mongoId" : "6a2c6cb474d8ee00a091abe8", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryBand" : "100k-150k", "hasSalary" : false, "allSkills" : [ "IOS development", "Mobile development", "Cross-platform development", "Reactive programming", "Unit testing", "Dependency injection", "Code review", "Continuous learning", "Teamwork", "Agentic AI", "IOS Development", "SwiftUI", "Product mindset", "Engineering fundamentals", "Planning sessions", "Retrospectives", "Daily standups", "Fintech", "Booking flow", "Recipients", "Pricing", "Payments", "Core banking", "Spend", "Compliance", "Claude Code", "Cursor", "Codex" ], "skillCount" : 28, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Junior", "dataQualityScore" : 1.0, "_score" : 630.9858, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "FinTech", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2a45ee74d8ee00a05d4128", "title" : "Forward Deployed Engineer, Infrastructure Specialist", "company" : "Cohere", "industry" : "Agentic Platform", "salary" : { "min" : 1.3E7, "max" : 1.8E7, "currency" : "JPY", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Forward Deployed Engineer, Infrastructure Specialist in Tokyo, Japan, adjusted for the technology industry and company size." }, "location" : "Tokyo", "locations" : [ "Tokyo" ], "timestamp" : "2026-06-14T21:05:32.512", "fingerprint" : "44cd95043e738759183234b96a1fe03a9751f1fa9765b54ee293f762d9e9adba", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/cohere/38f75a48-199c-4325-a7f8-2af6ed6a1b3b/application", "externalId" : "38f75a48-199c-4325-a7f8-2af6ed6a1b3b", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Tokyo", "country" : "Japan", "continent" : "as", "source" : "llm", "workMode" : "onsite", "geo" : "35.6768601,139.7638947" } ], "locationText" : "Tokyo, Japan", "employmentType" : "FULL_TIME", "technicalSkills" : "Kubernetes, Helm, Azure, AWS, GCP, Git", "professionalSkills" : [ "Data management", "Security requirements", "Deployment strategies" ], "hardSkillsList" : [ "Infrastructure assessment", "Technical troubleshooting" ], "hardSkills" : [ { "name" : "Infrastructure assessment", "level" : "intermediate" }, { "name" : "Technical troubleshooting", "level" : "intermediate" } ], "majorSkills" : "Infrastructure deployment, Customer engagement, Agentic AI", "majorSkillsList" : [ "Infrastructure deployment", "Customer engagement", "Agentic AI" ], "coreResponsibilities" : "Lead end-to-end deployment, Partner with IT teams, Assess infrastructure, Assess security requirements, Assess data management practices, Experiment with high velocity, Experiment with high quality, Engage customers, Deliver solutions, Design deployment strategies, Implement deployment strategies, Ensure compliance, Troubleshoot deployment issues, Resolve deployment issues, Provide timely solutions", "teamCollaboration" : "Enterprise IT teams; Client engineering teams", "domainKnowledge" : "Private cloud; On-premises environments; Data privacy; Security standards; Agentic AI", "domainList" : [ "private-cloud", "on-premises-environments", "data-privacy", "security-standards", "agentic-ai" ], "domainSpecificKnowledge" : [ "Private cloud", "On-premises environments", "Data privacy", "Security standards", "Agentic AI" ], "toolProficiency" : [ "Kubernetes", "Helm", "Git" ], "continuousLearning" : "Education stipend", "problemSolvingSkills" : "Troubleshooting", "specialRequirements" : "20-40% travel", "outcomesObjectives" : "Deliver solutions that exceed expectations", "qualificationsBasic" : "Experience deploying enterprise software, Administer production Kubernetes clusters, Expertise with Helm, Expertise in cloud infrastructure, Expertise in networking, Expertise in virtualization, Fluent Japanese, Business-level English", "qualificationsPreferred" : "Experience working directly with customers, Familiarity with DevOps practices, Familiarity with CI/CD pipelines, Familiarity with Git", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us! ABOUT NORTH: North https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications. WHY THIS ROLE? This role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. Our esteemed clients include industry leaders like RBC, Dell, and LG CNS. We are seeking engineers who deeply care about customers and want to work at the cutting edge of Agentic AI. Note: between 20 - 40% travel anticipated In this role, you will: - Lead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rollout. - Partner with enterprise IT teams to assess infrastructure, security requirements, and data management practices. - Experiment at a high velocity and with a high level of quality to engage our customers and ultimately deliver solutions that exceed their expectations - Design and implement deployment strategies tailored to client needs, ensuring compliance with data privacy and security standards. - Troubleshoot and resolve deployment-related technical issues, providing timely solutions to minimize downtime. You may be a good fit if: - You have experience with and enjoy working directly with customers - You have experience deploying enterprise software in private/hybrid cloud environments - You have proven experience administering production Kubernetes clusters and expertise with Helm - Familiarity with DevOps practices, CI/CD pipelines, and tools like Git for version control - You have strong expertise in cloud infrastructure (Azure, AWS, GCP), networking, and virtualization - You excel in fast-paced environments and can execute while priorities and objectives are a moving target - You have fluent Japanese and business-level English If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form https://docs.google.com/forms/d/12a6IrLdF3kI2nonKSr4tiFuz18rLQbaeYV-JM9L4o9Q/edit, and we will work together to meet your needs. We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider. Full-Time Employees at Cohere Enjoy These Perks: - An open and inclusive culture and work environment - Work closely with a team on the cutting edge of AI research - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch. - Full health and dental benefits, including a separate budget for mental health. - RRSP matching, 401K, Pension Scheme. - 100% Parental Leave top-up for up to 6 months, for either parent. - Annual enrichment benefits: - Arts & culture, fitness/wellness, quality time, and a workspace improvement credit. - Education & learning stipend for conferences, courses, and coaching. - Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend - 6 weeks of paid vacation (30 working days!) - Budget for traveling to other offices if you are remote, plus an annual company offsite. How and Where We Work: - Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon. - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events. - For those not near an office: a co-working benefit so you can work alongside others in your city. - Everyone receives a $500 home office stipend to set up your workspace properly.", "summaryDescription" : "Forward Deployed Engineer, Infrastructure Specialist at Cohere. Skills: Infrastructure deployment, Customer engagement, Agentic AI. Lead end-to-end deployment. 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Engineering teams; API platform; Security teams; Partner-facing organizations; Identity teams; Authorization teams; Data teams; Access Experience teams; Ads Agent Orchestrator team; Developer Experience; Partner Enablement", "projectManagementSkills" : [ "Roadmap strategy", "Roadmap definition" ], "domainKnowledge" : "Agent identity; Agent authorization; AI agents; Agent registry; Authentication flows; Capability-scoped authorization; Advertiser controls; Audit trail; Agentic commerce; M2M auth; Short-lived tokens; OAuth extensions; Identity and access management", "domainList" : [ "agent-identity", "agent-authorization", "ai-agents", "agent-registry", "authentication-flows", "capability-scoped-authorization", "advertiser-controls", "audit-trail", "agentic-commerce", "m2m-auth", "short-lived-tokens", "oauth-extensions", "identity-and-access-management" ], "domainSpecificKnowledge" : [ "Agent identity", "Agent authorization", "AI agents", "Agent registry", "Authentication flows", "Capability-scoped authorization", "Advertiser controls", "Audit trail", "Agentic commerce", "M2M auth", "Short-lived tokens", "OAuth extensions", "Identity and access management" ], "toolProficiency" : [ "Tableau", "Qlikview", "QuickSight" ], "communicationSkills" : "Customer value propositions; Executive-level prioritization", "documentationSkills" : "PRFAQs; BRDs; Technical specifications", "problemSolvingSkills" : "Feature delivery and tradeoffs", "outcomesObjectives" : "Agent adoption; Authorization accuracy; Advertiser control adoption; Developer onboarding time", "qualificationsBasic" : "2+ years end to end product delivery, 5+ years technical product management, Bachelor's degree, Contribute to engineering discussions, Feature delivery and tradeoffs, Own/drive roadmap strategy, Manage technical products, Represent and advocate customers", "qualificationsPreferred" : "Experience using analytical tools, Building and driving adoption, Software development experience, Experience deploying IAM systems, Experience in web security, Experience with web-based applications", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "As AI agents become the primary interface for advertisers and partners on Amazon Ads, we are building agent-native identity and authorization infrastructure that treats AI agents as first-class participants. We believe every agent should have a unique identity, authenticate through purpose-built flows, receive only the permissions its declared purpose requires, and produce a complete audit trail of every action it takes. We're looking for a Senior Product Manager – Technical (PMT) to define and drive the product strategy for Agent Identity and Authorization Infrastructure within Amazon Ads. You will own the roadmap for how 5,000+ partners and 2M+ advertisers grant, scope, and govern AI agent access to their advertising accounts — spanning agent registry, authentication, capability-scoped authorization, advertiser-facing controls, and auditability. This is a greenfield opportunity to define the trust layer for agentic commerce at Amazon scale. Key job responsibilities - Own the end-to-end product vision and roadmap for agent identity, authentication, and authorization — from 1P agent registry through 3P developer SDK and advertiser-facing access controls - Define product requirements for capability-scoped authorization models that go beyond tool-level access to intent-bound, time-bound, and data-bound delegation - Drive cross-functional alignment across 10+ engineering teams, API platform, security, and partner-facing organizations to deliver integrated agent trust infrastructure - Author PRFAQs, BRDs, and technical specifications for new authorization primitives (agent-to-agent delegation, programmable delegation tokens, spend controls, circuit breakers) - Define and track success metrics including agent adoption, authorization accuracy, advertiser control adoption, and developer onboarding time - Represent advertiser and partner needs in executive-level prioritization, translating complex authorization concepts into clear customer value propositions - Partner with engineering to make build/buy/integrate decisions on authentication protocols (M2M auth, short-lived tokens, OAuth extensions for agents) - Drive beta programs with external partners (agencies, integrators) to validate product-market fit before scaled rollout A day in the life You'll start your day reviewing agent adoption metrics and authorization error rates across 1P and 3P surfaces. You might spend the morning in a design review with engineers debating whether capability-scoped permissions should be enforced at the gateway or service layer. After lunch, you're leading a working session with a large agency partner (like PacVue or Teikametrics) to understand how they want to register and manage multiple specialized agents under their application. In the afternoon, you're writing the product spec for the advertiser-facing Agent Access UI — where advertisers see every authorized agent, scope what each can do, and revoke access instantly. You close the day aligning with your VP on the 3P agent sandbox launch timeline for unBoxed. Your internal stakeholders include engineering (Identity, Authorization, Data, and Access Experience teams), the Ads Agent Orchestrator team, Developer Experience (DX), and Partner Enablement. Your customers are advertisers who need control over AI agents accessing their accounts, partners building agentic integrations, and internal 1P agent teams shipping skills on the Ads Agent platform. About the team The Ads Agent Identity and Authorization Infrastructure (AI²) team owns identity and access management for Amazon Ads — for both humans and AI agents. We manage registration, account management, permission controls, and ad-product eligibility that serve as gateways to Amazon Ads, impacting 5K+ partners and 2M+ advertisers globally with 800K+ registrations per year and 5M+ active users. We are a team of builders who ship at high velocity — we launched agent registry and agent authorization for 1P agents in Q1 2026, and are now extending to 3P. We value customer obsession (advertisers must trust the agents acting on their behalf), ownership (you own the product end-to-end from vision through metrics), and bias for action (we ship iteratively with real partners, not in isolation). We are based in New York (JFK19). Basic Qualifications: - 2+ years of end to end product delivery experience - 5+ years of technical product or program management experience - Bachelor's degree - Experience contributing to engineering discussions around technology decisions and strategy related to a product - Experience with feature delivery and tradeoffs of a product - Experience owning/driving roadmap strategy and definition - Experience managing technical products or online services - Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning Preferred Qualifications: - Experience in using analytical tools, such as Tableau, Qlikview, QuickSight - Experience in building and driving adoption of new tools - Experience in software development, or experience working with REST API based services - Experience in deploying identity and access management systems, or experience in web security and experience with web-based applications and HTTP Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 166,300.00 - 225,000.00 USD annually", "summaryDescription" : "Senior PMT, Ads Agent Identity and Authorization Infrastructure at Amazon.com Services LLC. Skills: Identity management, Access management, Authorization infrastructure. Own product vision and roadmap. 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"skillCount" : 0, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "mid", "dataQualityScore" : 0.5555556, "_score" : 613.8167, "daysOld" : 6, "hasLocation" : true, "hasGeo" : false, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 }, { "id" : "6a2c6a8f74d8ee00a090c9a2", "title" : "Engineer, Enterprise Service Desk", "company" : "ABACUS", "industry" : "Technology", "salary" : { "min" : 105000.0, "max" : 145000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Engineer, Enterprise Service Desk in Atlanta, United States, adjusted for the technology industry and company size." }, "location" : "Atlanta, Georgia, United States", "locations" : [ "Atlanta", "Georgia", "United States", "Charlotte", "North Carolina", "United States", "Columbus", "Ohio", "United States", "Fort Lauderdale", "Florida", "United States", "Newark", "New Jersey", "United States", "Orlando", "Florida", "United States" ], "certifications" : [ "MCSA: Server Infrastructure (70-410, 70-411, 70-412)", "MCSA: O365 (MS-100, MS-101)" ], "timestamp" : "2026-06-16T05:07:01.471", "fingerprint" : "853633c327f1f60288021872b1e9346e3315fc7a96592979f0ea5cac56bbaa36", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://abacustechnology.com/about/careers/current-vacancies/?gh_jid=7746420003", "externalId" : "7746420003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Atlanta", "state" : "Georgia", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "hybrid", "geo" : "33.7544657,-84.3898151" } ], "locationText" : "Atlanta, Georgia, United States", "minimumEducation" : "Associate's", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "VMWare ESXi, Hyper-V, Active Directory, SQL, SharePoint, Exchange Servers, Backup Technologies, VMWare, Citrix, VPN, Terminal Services, VoIP", "professionalSkills" : [ "System design", "Solution delivery", "Process improvement" ], "hardSkillsList" : [ "Server configuration", "Virtualization", "Network configuration", "Security hardening", "Cable management", "Backup testing", "Restore testing", "Malware mediation", "Ransomware mediation", "Virus mediation" ], "softSkillsList" : [ "Adaptability", "Leadership" ], "hardSkills" : [ { "name" : "Server configuration", "level" : "intermediate" }, { "name" : "Virtualization", "level" : "intermediate" }, { "name" : "Network configuration", "level" : "intermediate" }, { "name" : "Security hardening", "level" : "intermediate" }, { "name" : "Cable management", "level" : "intermediate" }, { "name" : "Backup testing", "level" : "intermediate" }, { "name" : "Restore testing", "level" : "intermediate" }, { "name" : "Malware mediation", "level" : "intermediate" }, { "name" : "Ransomware mediation", "level" : "intermediate" }, { "name" : "Virus mediation", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Adaptability" }, { "name" : "Leadership" } ], "majorSkills" : "Enterprise Service Desk, Cloud environments, On premise infrastructure, Telephony systems", "majorSkillsList" : [ "Enterprise Service Desk", "Cloud environments", "On premise infrastructure", "Telephony systems" ], "coreResponsibilities" : "Design customer facing systems, Implement customer facing systems, Design internal systems, Implement internal systems, Provide world class client experience, Provide escalation support, Deliver excellent customer experience, Resolve service tickets, Resolve escalated service tickets, Provide guidance for aging issues, Resolve aging issues, Provide guidance for complex issues, Resolve complex issues, Assist clients with design, Assist clients with implementation, Assist clients with installation, Assist clients with configuration, Assist clients with usability, Troubleshoot client emergencies, Resolve client emergencies, Work with vendor representatives, Resolve software issues, Resolve hardware issues, Install Microsoft Server Operating Systems, Upgrade Microsoft Server Operating Systems, Perform virus mediation, Perform malware mediation, Perform ransomware mediation, Provide server room cable management, Create detailed documentation, Maintain detailed documentation, Resolve backup issues, Perform restore testing, Notify Client Success Managers, Install virtual environments, Configure virtual environments, Support virtual environments, Harden security posture, Communicate with clients, Inform clients of incident progress, Notify clients of impending changes, Notify clients of agreed outages, Coordinate activities with client, Assist with client training, Comply with safety requirements, Complete required training, Follow MIT policies, Follow MIT procedures, Follow MIT field guidelines, Follow MIT reporting requirements, Follow MIT technical advisories, Demonstrate pro-active approach toward safety, Demonstrate pro-active approach toward health, Demonstrate pro-active approach toward quality, Lead teams on large projects, Lead teams on complex projects, Participate in project planning, Participate in solution delivery, Mentor team members, Teach improved processes, Serve as escalation point, Mentor all team members, Prepare staff training material, Deliver staff training material, Advance skills of technical team, Follow Abacus's defined processes, Follow Abacus's policies, Follow Abacus's service delivery standards, Perform other duties assigned", "teamCollaboration" : "Escalation support; Client Success Managers; Team members; Staff training", "projectManagementSkills" : [ "Project planning", "Solution delivery" ], "domainKnowledge" : "Public cloud environments; Private cloud environments; On premise infrastructure; Telephony systems; Microsoft Environments; Windows Servers; Virtual environments; High Availability; Security posture; Abacus standards; Company requirements; Customer requirements; System 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], "communicationSkills" : "Client communication; Incident progress; Impending changes; Agreed outages; Staff training", "documentationSkills" : "Detailed documentation", "continuousLearning" : "Learn new technology skills", "problemSolvingSkills" : "Problem solving; Troubleshooting; Root cause analysis", "specialRequirements" : "Commute to office", "outcomesObjectives" : "Continued customer satisfaction", "qualificationsBasic" : "5+ years Systems Engineer, MCSA: Server Infrastructure, MCSA: O365, Windows 2016/2012/2008 servers, Active Directory, SQL, SharePoint, Exchange Servers, Backup Technologies, Internet/DNS/E-mail/Communication issues, VMWare, Citrix, VPN, Terminal Services, VoIP, Voicemail, Analog hardware/software, Vendor specific hardware/software, Problem solving skills, Client relationship skills, Verbal communication skills, Written communication skills, Learn and retain new technology skills, Troubleshooting processes, Maintain calm, Present professionally in high stress situations", "qualificationsPreferred" : "MSP specific experience", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Job Summary: Abacus’s Engineer, Enterprise Service Desk role is responsible for the design and implementation of customer facing and internal systems, including public and private cloud environments as well as on premise infrastructure and telephony systems, all while providing a world class client experience daily. In addition to leading projects, Level Threes provide escalation support to all service delivery team members. Responsibilities (including, but not limited to): Deliver an excellent customer experience in all interactions Resolve new and escalated service tickets, provide guidance for or personally resolve aging and complex issues Assist clients with the design and implementation, installation, configuration and ongoing usability of desktop computers, mobile devices, peripheral equipment, telephony systems, servers, storage, networking and software Troubleshoot and resolve client emergencies with minimal oversight, persevering until resolved Work with vendor representatives to resolve software and hardware issues Install and/or upgrade Microsoft Server Operating Systems Perform advanced virus, malware and ransomware mediation Provide professional quality server room cable management Responsible for creating and maintaining high quality, detailed documentation Resolve complex backup issues and perform restore testing Notifies Client Success Managers when outdated equipment causes repeated issues Install, configure, support complex virtual environments with High Availability in VMWare ESXi and Hyper-V environments Work with clients to harden security posture through policy and advanced technologies according to Abacus standards and processes Communicate with clients as required: Keeping them informed of incident progress, notifying them of impending changes or agreed upon outages Accountable for continued customer satisfaction and coordinates all activities with the client, assists with client training while representing MIT in a professional manner Exhibit adaptability and is willing to alter shifts and job requirements to meet the needs of clients and Abacus Comply with all safety requirements, including but not limited to: completing all required training, following all guidance provided in MIT policies, procedures, field guidelines, reporting requirements, and technical advisories. Demonstrates a pro-active approach toward safety, health, and quality in compliance with all Company, governmental and customer requirements Lead teams on large, complex projects (i. e. system migrations, virtual server configurations with high availability, server and firewall installations, VPN tunnel configurations, SAN setups, etc.) Participate in project planning, solution delivery, mentoring and teaching improved processes to team members Serve as an escalation point to mentor all team members Prepare and deliver staff training material to advance the skills of the technical team Follow Abacus's defined processes, policies, service delivery standards All other duties assigned Qualifications and Education Requirements: Associates degree in technology related field OR equivalent combination of education and work experience A minimum of 5+ years of as a Systems Engineer or similar role, working in Microsoft Environments Required certifications: MCSA: Server Infrastructure (70-410, 70-411, 70-412) or equivalent, MCSA: O365 (MS-100, MS-101), business and leadership experience Strong understanding of Windows 2016/2012/2008 servers, Active Directory, SQL, SharePoint, Exchange Servers, Backup Technologies, Internet/DNS/E-mail/Communication issues Strong working knowledge of VMWare, Citrix, VPN and Terminal Services Strong working knowledge of VoIP, voicemail, analog, and vendor specific hardware/software Excellent problem solving and client relationship skills Excellent verbal and written communication skills Ability to learn and retain new technology skills and troubleshooting processes, team player ,maintain calm and present yourself professionally in high stress situations MSP specific experience strongly desired Ability to commute to office on a hybrid basis", "summaryDescription" : "Engineer, Enterprise Service Desk at ABACUS. 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: "Austin, Texas, USA", "locations" : [ "Austin, Texas, USA" ], "timestamp" : "2026-06-15T03:16:48.268", "fingerprint" : "822d7b3c89907002f30cf210176dd937976622ed8226376b9cf88fbef3deba21", "source" : "amazon", "language" : "en", "applyUrl" : "https://account.amazon.com/jobs/10384250/apply", "externalId" : "bdf45fc8-f6d3-4a1f-b5d8-65b9cd3b01cf", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Austin", "state" : "Texas", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "30.2711286,-97.7436995" } ], "locationText" : "Austin, Texas, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "AI, Machine Learning, Agentic architectures, Conversational AI, RAG pipelines, Multi-agent orchestration", "professionalSkills" : [ "Product strategy", "Roadmap definition", "Customer research", "Hypothesis validation", "Implementation planning", "Prioritization", "Phased rollouts", "Use case definition", "KPI definition", "Tradeoff conversations", "Product development", "Product culture", "Product management frameworks" ], "hardSkillsList" : [ "Security products", "Enterprise security", "AI-powered products", "Cloud-agnostic security", "Security tooling", "Security practitioners", "CISOs", "Enterprise teams", "AI tools", "AI techniques", "Multi-cloud security", "Cloud environments" ], "softSkillsList" : [ "Customer obsession", "Builder's mindset", "Owner's mentality" ], "hardSkills" : [ { "name" : "Security products", "level" : "intermediate" }, { "name" : "Enterprise security", "level" : "intermediate" }, { "name" : "AI-powered products", "level" : "intermediate" }, { "name" : "Cloud-agnostic security", "level" : "intermediate" }, { "name" : "Security tooling", "level" : "intermediate" }, { "name" : "Security practitioners", "level" : "intermediate" }, { "name" : "CISOs", "level" : "intermediate" }, { "name" : "Enterprise teams", "level" : "intermediate" }, { "name" : "AI tools", "level" : "intermediate" }, { "name" : "AI techniques", "level" : "intermediate" }, { "name" : "Multi-cloud security", "level" : "intermediate" }, { "name" : "Cloud environments", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Customer obsession" }, { "name" : "Builder's mindset" }, { "name" : "Owner's mentality" } ], "majorSkills" : "Product strategy, AI-first product thinking, Enterprise security", "majorSkillsList" : [ "Product strategy", "AI-first product thinking", "Enterprise security" ], "coreResponsibilities" : "Own product strategy and vision, Drive roadmap for AI-powered security products, Understand security practitioners, CISOs, enterprise teams, Conduct customer research, Validate hypotheses, Translate pain points into products, Drive AI-first product thinking, Lead implementation planning, Lead prioritization, Lead phased rollouts, Write product requirements, Define use cases, Define KPIs, Drive tradeoff conversations, Partner with engineers, Partner with applied scientists, Partner with UX designers, Partner with security researchers, Partner with leadership, Prototype, Validate, Iterate, Leverage AI tools, Accelerate research, Synthesize insights, Generate artifacts, Define multi-cloud story, Synthesize security technologies, Build product culture, Establish rituals, Establish frameworks", "teamCollaboration" : "Cross-functional teams; Engineers; Applied scientists; UX designers; Security researchers; Leadership", "projectManagementSkills" : [ "Roadmap strategy", "Roadmap definition", "Implementation planning", "Prioritization", "Phased rollouts" ], "domainKnowledge" : "Enterprise security; Cloud-agnostic security; Agentic architectures; Conversational AI; Multi-cloud security", "domainList" : [ "enterprise-security", "cloud-agnostic-security", "agentic-architectures", "conversational-ai", "multi-cloud-security" ], "domainSpecificKnowledge" : [ "Enterprise security", "Cloud-agnostic security", "Agentic architectures", "Conversational AI", "Multi-cloud security" ], "toolProficiency" : [ "AI tools" ], "documentationSkills" : "Product requirements", "innovationCreativity" : "AI-first team; Startup speed; What if we could energy; Builder's mindset; Experimental AI tools", "problemSolvingSkills" : "Ambiguous customer problems; Tradeoff conversations; Synthesize insights", "outcomesObjectives" : "Ship products; Shape products; Protect customers wherever they are", "qualificationsBasic" : "5+ years product management experience, Experience owning/driving roadmap strategy, Experience contributing to engineering discussions, Experience advocating for customers, Experience managing feature delivery, Experience managing customers in early beta, Experience with SaaS and enterprise security products, Familiarity with AI-first development practices, Familiarity with agentic architectures, Familiarity with conversational AI product experiences", "qualificationsPreferred" : "Experience with AI/ML technologies, Experience launching 0-to-1 products, Experience using AI tools, Experience making architectural tradeoff decisions, Experience with analytical tools", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "What happens when you hand a product manager the keys to an AI-first team that opperates like a start up at Amazon scale? They build the future of security. Want in? Amazon Enterprise Security Products is a newly launched group building intelligent, cloud-agnostic security tools where AI isn't a buzzword on a roadmap slide — it's how we think, build, and ship. We need a Product Manager - Tech who can move at startup speed, obsess over customers, and shape products that don't exist yet, all at a scale most startups only dream about. This is not a \"write requirements and wait\" PM role. You'll be in the room (and in the code reviews) with engineers, security researchers, and applied scientists, turning ambiguous customer problems into shipped products. You'll define what we build, why we build it, and how fast it gets to customers. Short feedback loops. Real ownership. No layers between you and the impact. Key job responsibilities * Own product strategy and vision end-to-end: Define and drive the roadmap for AI-powered security products from zero-to-one and beyond. You're not inheriting a backlog; you're creating the product direction for a team that's building the future of enterprise security tooling. * Be the customer obsession engine: Deeply understand the security practitioners, CISOs, and enterprise teams we serve. Conduct ongoing customer research, validate hypotheses fast, and translate pain points into products people actually want to use not just products they're told to use. * Drive AI-first product thinking: You don't need to write the model, but you need to understand what agentic architectures, conversational interfaces, RAG pipelines, and multi-agent orchestration make possible; and translate that into product experiences that feel like magic to customers. Stay ahead of what's emerging and experimental; bring the \"what if we could…\" energy every day. * Ship like a startup, plan like a strategist: Lead implementation planning, prioritization, and phased rollouts alongside engineering. Write crisp product requirements that drive agentic development processes, define use cases and KPIs, and drive the hard tradeoff conversations. You own outcomes with the autonomy and accountability that comes with a high-trust, small team. * Partner across disciplines with zero friction: Work shoulder-to-shoulder with engineers, applied scientists, UX designers, security researchers, and leadership. Small team means your voice shapes direction immediately. The best idea wins here, regardless of title or tenure. * Prototype, validate, iterate — relentlessly: Bring a builder's mindset to product management. Leverage AI tools and techniques (yes, even the experimental ones) to accelerate research, synthesize insights, generate artifacts, and move faster than any PM org you've been part of before. * Define the multi-cloud, cloud-agnostic story: Understand and synthesize security technologies across AWS and competing cloud environments. Our customers operate everywhere, your product strategy needs to protect them wherever they are. * Build the product culture from the ground floor: You're not joining a mature PM org, you're helping define what product management looks like on a fast-growing, AI-first team. Establish the rituals, the frameworks, and the bar. In the process, you become the kind of PM who has shaped a product category, scaled a team, and defined how modern security software gets built. A day in the life No two days look the same and that's the point. You might start your morning reviewing customer interview notes and reshaping a feature spec using AI-assisted writing tools, then jump into a design session where your product instincts collide with a principal engineer's architecture vision (and something better emerges). After lunch, you're demoing a prototype to a customer, pressure-testing assumptions in real time. By end of day, you've reprioritized a sprint based on what you learned, drafted a strategy doc for a new capability no one's built before, and pinged the team with three ideas you had on your walk. Your work reaches production fast and you see customers react in real time, not quarters later. About the team Amazon Enterprise Security Products is built by builders who tackle challenges others might consider too ambitious. We're a small team where there are no layers between you and the decision, no waiting quarters to see your work reach customers. Every team member brings an owner's mentality. If there's a problem worth solving, we solve it. No mission is beyond reach, no detail beneath our attention. We move fast, we ship fast, and we learn from what we ship. This is where builders, who want to make the impossible routine, come to do their best work. Diverse Experiences Amazon Security values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve. Basic Qualifications: - Experience owning/driving roadmap strategy and definition - Experience contributing to engineering discussions around technology decisions and strategy related to a product - Experience in representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning - 5+ years of non-internship product management experience in commercial B2B technical products or online services - Experience managing feature delivery, tradeoffs, and prioritization across cross-functional teams - Experience managing customers in early beta - Experience with SaaS and enterprise security products - Familiarity with AI-first development practices, agentic architectures, or conversational AI product experiences Preferred Qualifications: - Experience with AI/ML technologies - Experience launching 0-to-1 products in ambiguous, fast-moving environments - Experience using AI tools to accelerate product management workflows (research synthesis, spec generation, competitive analysis, etc.) - Experience making architectural tradeoff decisions alongside engineering teams - Experience with analytical tools Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, TX, Austin - 151,200.00 - 204,600.00 USD annually", "summaryDescription" : "Sr Product Manager - Tech, Enterprise Security Products at Amazon.com Services LLC. Skills: Product strategy, AI-first product thinking, Enterprise security. Own product strategy and vision. Drive roadmap for AI-powered security products", "postedDate" : "2026-06-13T10:19:59.187", "createdAt" : "2026-06-13T10:19:59.187", "lastUpdated" : "2026-06-15T03:16:48.268", "ingestTimestamp" : "2026-06-13T10:19:59.187", "mongoId" : "69d5e4982beec4dd3d931b10", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/10384250/apply", "salaryAnnualMin" : 151000, "salaryAnnualMax" : 204600, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "Security products", "Enterprise security", "AI-powered products", "Cloud-agnostic security", "Security tooling", "Security practitioners", "CISOs", "Enterprise teams", "AI tools", "AI techniques", "Multi-cloud security", "Cloud environments", "Customer obsession", "Builder's mindset", "Owner's mentality", "Product strategy", "AI-first product thinking", "Roadmap definition", "Customer research", "Hypothesis validation", "Implementation planning", "Prioritization", "Phased rollouts", "Use case definition", "KPI definition", "Tradeoff conversations", "Product development", "Product culture", "Product management frameworks", "Roadmap strategy", "Agentic architectures", "Conversational AI" ], "skillCount" : 32, "jobCategory" : "project-management", "dataQualityScore" : 1.0, "_score" : 611.6375, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology" }, { "id" : "6a2ca16074d8ee00a09a548d", "title" : "Enterprise Account Executive", "company" : "Benchling", "industry" : "Sales", "salary" : { "min" : 140000.0, "max" : 200000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "Boston, MA", "locations" : [ "Boston, MA", "New York, NY", "Philadelphia, PA" ], "timestamp" : "2026-06-15T07:57:44.019", "fingerprint" : "258936c6b06e515f3cb0f1459278bc4a3920b0bc48e76417aa7b9c5ced68b74c", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/benchling/77e774c8-b0ed-4a87-8e25-60f9a0105f62/application", "externalId" : "77e774c8-b0ed-4a87-8e25-60f9a0105f62", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Boston", "state" : "Massachusetts", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "42.3588336,-71.0578303" } ], "locationText" : "Boston, Massachusetts, United States", "employmentType" : "FULL_TIME", "professionalSkills" : [ "Solution selling", "Account management", "Pipeline generation", "Sales forecasting", "Negotiation", "Closing deals" ], "hardSkillsList" : [ "Sales forecasting", "MEDDICC methodology" ], "hardSkills" : [ { "name" : "Sales forecasting", "level" : "intermediate" }, { "name" : "MEDDICC methodology", "level" : "intermediate" } ], "majorSkills" : "Enterprise sales, SaaS sales, Pipeline generation, Sales forecasting", "majorSkillsList" : [ "Enterprise sales", "SaaS sales", "Pipeline generation", "Sales forecasting" ], "coreResponsibilities" : "Generate pipeline, Identify new business opportunities, Engage with multiple personas, Generate leads, Move leads through sales cycle, Develop accurate sales forecasts, Maintain accurate sales forecasts, Inform decision-making with data, Ensure predictable revenue outcomes, Attain revenue targets, Communicate platform value, Tailor presentations, Tailor proposals, Lead negotiations, Address key stakeholders, Navigate organizational complexities, Address objections, Secure new business agreements, Understand unique needs, Align solutions with objectives, Partner with internal teams, Partner with external teams, Ensure seamless client experience, Drive customer satisfaction, Stay informed on industry trends, Stay informed on competitors, Stay informed on emerging technologies, Drive sales process, Build champions, Maintain account integrity, Maintain opportunity data", "teamCollaboration" : "Partner with SDRs; Partner with marketing; Partner with product; Partner with customer success; Partner with GSIs; Partner with AWS", "domainKnowledge" : "Biotech R&D; Data management; Workflow SaaS; AI platform", "domainList" : [ "biotech-r-d", "data-management", "workflow-saas", "ai-platform" ], "domainSpecificKnowledge" : [ "Biotech R&D", "Data management", "Workflow SaaS", "AI platform" ], "toolProficiency" : [ "Salesforce" ], "communicationSkills" : "Tailoring presentations; Tailoring proposals", "continuousLearning" : "Stay informed on industry trends; Stay informed on competitors; Stay informed on emerging technologies", "outcomesObjectives" : "Meet revenue targets; Exceed revenue targets; Secure new business agreements", "qualificationsBasic" : "Proven enterprise/major accounts seller, Data management/workflow SaaS experience, Drive pipeline generation, Manage complex sales cycles, 7+ figure deals, Sales forecasting skills, Meet or exceed targets, Sell outside pre-established budgets, Build compelling business case, Influence purchasing decisions, Work with diverse personas, Influence decision-making at all levels, Dynamic communication skills, Negotiation skills, Interpersonal skills, Work independently, Work collaboratively", "qualificationsPreferred" : "MEDDICC sales methodology", "remoteFriendly" : true, "workSiteFlexibility" : "Flexible", "rawDescription" : "We are rebuilding biotech for the AI era. When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps. AI has the potential to change this, compressing decades of R&D work into years. But that only happens when clean, structured scientific data and AI are built into how science gets done. Benchling is the AI platform for biotech R&D. Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows. Over 200,000 scientists around the world trust Benchling to power their most important work, from academic labs to Sanofi, Moderna, and more than half of the world's top 50 biopharma. We’re building an AI scientist for our customers. We can’t do that if we haven’t built the muscle ourselves. AI fluency is the foundation we build on; it's core to how we work, and we're committed to helping every new hire integrate it into their day-to-day. As part of our interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today. ROLE OVERVIEW We are seeking a motivated and results-driven Enterprise Account Executive to join our Enterprise team. In this role, you will be responsible for driving new business into different lines of business within your designated 1-3 of the Top 50 global accounts, focusing on building and maintaining strong relationships with key stakeholders across various personas within an account (IT, Science/R&D, Data Science). You will play a crucial role in expanding our customer base and ensuring successful sales outcomes through effective pipeline generation and accurate sales forecasting. RESPONSIBILITIES - Pipeline Generation: Creating 80% of your pipeline by identifying new business opportunities and engaging with multiple personas within the prospect/customer base in partnership with your SDR. Utilize various strategies and tools to generate leads and move them through the sales cycle. - Sales Forecasting: Develop and maintain accurate sales forecasts (+/- 10 of goal),, leveraging data to inform decision-making and ensure predictable revenue outcomes with the goal of consistent attainment of revenue targets. - Solution Selling: Effectively communicate the value of our platform, tailoring presentations and proposals to meet the specific needs of each prospect. - Negotiation and Closing: Lead negotiations with potential clients, by thoughtfully addressing key stakeholders including multiple personas and CxO in the buyer journey, while navigating organizational complexities, addressing objections and securing new business agreements. - Account Management: Work across multiple personas within an account to understand their unique needs and align Benchling’s solutions with their business objectives. - Collaboration: Partner with internal teams (marketing, product, customer success, etc) and external teams (GSIs, AWS, etc) to ensure a seamless experience for clients and drive long-term customer satisfaction. - Continuous Learning: Stay informed about industry trends, competitors, and emerging technologies to maintain a competitive edge in the market. You are a curious learner who is striving to elevate their craft to the next level. - Process: Drive the sales process through Pipeline Generation (PG), Leading Indicators to drive repeatable success, 3 Why’s/MEDDICC & ability to build champions across the user community, middle management & ‘C’ Suite. Maintain account integrity and opportunity data within company systems; Salesforce. QUALIFICATIONS You are drawn to our mission and you want to help Benchling win new business across your respective accounts. You are committed to working in a collaborative environment, working together as a team. You have a love for working in a fast-paced startup/pre IPO environment and taking the initiative to get stuff done and try new things. You are passionate about powering new possibilities in biotech faster. - Proven experience as a global enterprise/major accounts seller, preferably within a data management, workflow SaaS or technology-driven environment that sells to multiple personas across IT & various Line of business. - Demonstrated ability to drive pipeline generation and manage complex sales cycles of 7+ figure deals. - Strong sales forecasting skills with a track record of meeting or exceeding targets. - Demonstrated success in selling products or solutions that typically fall outside of pre-established budgets, with a proven ability to build a compelling business case and influence purchasing decisions. - Experience working with diverse personas within an account (from technical decision makers, business decision makers & CxO execs), with the ability to influence decision-making at all the levels. - Dynamic communication, negotiation, and interpersonal skills. - Self-motivated, with a strong drive to achieve and exceed goals. - Ability to work independently as well as collaboratively in a team environment. - Ability to leverage the MEDDICC sales methodology is highly recommended - Knowledge of the life sciences industry, including: R&D, and/or IT functions is preferred but not required. #LI-Remote #BI-Remote #LI-SF1 Benchling welcomes everyone. We believe diversity enriches our team so we hire people with a wide range of identities, backgrounds, and experiences. We are an equal opportunity employer. That means we don’t discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We also consider for employment qualified applicants with arrest and conviction records, consistent with applicable federal, state and local law, including but not limited to the San Francisco Fair Chance Ordinance.", "summaryDescription" : "Enterprise Account Executive at Benchling. Skills: Enterprise sales, SaaS sales, Pipeline generation, Sales forecasting. Generate pipeline. 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Across engineering teams; Cross-functional agile teams", "projectManagementSkills" : [ "Agile development environment" ], "domainKnowledge" : "Device OS; Infrastructure; Cloud platforms; Distributed systems; Software development lifecycle; Security best practices", "domainList" : [ "device-os", "infrastructure", "cloud-platforms", "distributed-systems", "software-development-lifecycle", "security-best-practices" ], "domainSpecificKnowledge" : [ "Device OS", "Infrastructure", "Cloud platforms", "Distributed systems", "Software development lifecycle", "Security best practices" ], "toolProficiency" : [ "CI/CD tools", "Docker", "Kubernetes", "AWS", "Azure", "GCP", "Ansible", "Terraform" ], "communicationSkills" : "English communication", "innovationCreativity" : "Architecting robust systems; Innovate faster; Design state-of-the-art automation solutions; Continuous technological advancement", "problemSolvingSkills" : "Solve complex technical challenges", "outcomesObjectives" : "Enhance developer productivity; Enhance system reliability; Optimize software development workflows; Proactively identify system challenges; Proactively resolve system challenges; Drive continuous technological advancement; Empower engineers to innovate faster; Streamline software development lifecycle", "qualificationsBasic" : "Bachelor's degree in Computer Science, 3+ years advanced scripting, Proficient with CI/CD tools, Proficient with infrastructure management, Understanding of Linux/Unix system administration, Excellent English communication skills, Ability to collaborate effectively", "qualificationsPreferred" : "Master's degree, Experience with containerization technologies, Experience with cloud platforms, Knowledge of monitoring tools, Knowledge of observability practices, Experience with infrastructure automation, Experience with configuration management tools, Understanding of software development lifecycle, Understanding of best practices, Experience with build systems, Experience with package management, Knowledge of security best practices, Experience supporting large-scale distributed systems, Experience working in agile development environment", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "Revolutionize developer productivity by building the critical infrastructure that powers Amazon's Device OS platform! Join a dynamic team where your technical expertise will directly accelerate software development across our global engineering ecosystem. Key job responsibilities - Design and implement sophisticated CI/CD pipelines that enhance developer productivity and system reliability - Develop intelligent automation tools to optimize software development workflows - Create robust monitoring and observability solutions that proactively identify and resolve system challenges - Collaborate across engineering teams to architect innovative infrastructure strategies - Research and integrate emerging technologies that drive continuous technological advancement A day in the life Imagine architecting robust systems that empower hundreds of engineers to innovate faster and more efficiently. You'll collaborate across teams, design state-of-the-art automation solutions, and solve complex technical challenges that streamline our software development lifecycle. About the team We are a passionate group of engineers dedicated to creating scalable, reliable tooling that transforms how software development happens at Amazon. Our team spans the United States and Mexico, united by a shared vision of technological excellence and continuous improvement. Basic Qualifications: - Bachelor's degree in Computer Science, Engineering, or related technical field - Demonstrated expertise in system engineering, DevOps, or software development - 3+ years of non-internship of advanced scripting and automation skills using Python, Bash, or PowerShell - Proficient with CI/CD tools and infrastructure management technologies - Strong understanding of Linux/Unix system administration - Excellent English communication skills (written and verbal communication) - Ability to collaborate effectively in a distributed team environment Preferred Qualifications: - Master's degree in Computer Science, Engineering, or related field - Experience with containerization technologies (Docker, Kubernetes) - Experience with cloud platforms and services (AWS, Azure, GCP) - Knowledge of monitoring and observability tools and practices - Experience with infrastructure automation and configuration management tools (Ansible, Terraform, etc.) - Understanding of software development lifecycle and best practices - Experience with build systems and package management - Knowledge of security best practices for development and deployment environments - Experience supporting large-scale distributed systems - Experience working in an agile development environment Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.", "summaryDescription" : "System Development Engineer, Device OS Infrastructure at Servicios Comerciales Amazon Mexico S. de R.L. de C.V.. Skills: System development, Device OS, Infrastructure, CI/CD pipelines, Automation tools. Design CI/CD pipelines. Implement CI/CD pipelines", "postedDate" : "2026-06-13T11:44:11.859", "createdAt" : "2026-06-13T11:44:11.859", "lastUpdated" : "2026-06-15T00:59:58.801", "ingestTimestamp" : "2026-06-13T11:44:11.859", "mongoId" : "68e6b1dd70f0b99d58d66ea5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://account.amazon.com/jobs/3102431/apply", "salaryBand" : "200k+", "hasSalary" : false, "allSkills" : [ "Scripting", "Automation", "System administration", "Containerization", "Cloud platforms", "Infrastructure automation", "Configuration management", "Software development lifecycle", "Security best practices", "Distributed systems", "System development", "Device OS", "Infrastructure", "CI/CD pipelines", "Automation tools", "System engineering", "DevOps", "Software development", "Infrastructure strategies", "Technological advancement", "Automation solutions", "System challenges", "Agile development environment", "CI/CD tools", "Docker", "Kubernetes", "AWS", "Azure", "GCP", "Ansible", "Terraform" ], "skillCount" : 31, "jobCategory" : "engineering", "dataQualityScore" : 1.0, "_score" : 608.95966, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2a54ec74d8ee00a06052fc", "title" : "Senior AI Infrastructure Engineer", "company" : "Stoke Space", "salary" : { "min" : 165000.0, "max" : 235000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for Senior AI Infrastructure Engineer in Kent, United States, adjusted for seniority and industry." }, "location" : "Kent, Washington, United States", "locations" : [ "Kent", "Washington", "United States" ], "timestamp" : "2026-06-14T22:16:06.716", "fingerprint" : "967f86ee70dcc75a5b2a6a6b5c87e20d575b5fca1c87b7055123b81f7f244757", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://stokespace.com/careers/current-openings?gh_jid=6016411004", "externalId" : "6016411004", "structuredLocations" : [ { "city" : "Kent", "state" : "Washington", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "47.3826903,-122.2270272" } ], "locationText" : "Kent, Washington, United States", "experienceMinYears" : 5, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "Python, TypeScript, Go, LLM, RAG, APIs, Webhooks, Event-driven patterns, AWS, Bedrock, Lambda, ECS, Fargate", "professionalSkills" : [ "Product instinct", "Systems integration", "Prompt engineering", "Evaluation methodologies", "Capacity planning", "Cost optimization", "Latency tuning", "Incident response", "Architectural decision making" ], "hardSkillsList" : [ "AI engineering", "Software development", "Intelligent automation", "Model gateways", "Vector stores", "Evaluation harnesses", "Observability", "Deployment pipelines", "Offline evals", "Online metrics", "Regression tracking", "Human-in-the-loop review", "Data telemetry", "Document stores", "Code repositories", "Business applications", "Data handling", "Access controls", "Prompt injection defenses", "ITAR/export-control considerations", "Runbooks" ], "softSkillsList" : [ "Ownership", "Self-direct" ], "hardSkills" : [ { "name" : "AI engineering", "level" : "intermediate" }, { "name" : "Software development", "level" : "intermediate" }, { "name" : "Intelligent automation", "level" : "intermediate" }, { "name" : "Model gateways", "level" : "intermediate" }, { "name" : "Vector stores", "level" : "intermediate" }, { "name" : "Evaluation harnesses", "level" : "intermediate" }, { "name" : "Observability", "level" : "intermediate" }, { "name" : "Deployment pipelines", "level" : "intermediate" }, { "name" : "Offline evals", "level" : "intermediate" }, { "name" : "Online metrics", "level" : "intermediate" }, { "name" : "Regression tracking", "level" : "intermediate" }, { "name" : "Human-in-the-loop review", "level" : "intermediate" }, { "name" : "Data telemetry", "level" : "intermediate" }, { "name" : "Document stores", "level" : "intermediate" }, { "name" : "Code repositories", "level" : "intermediate" }, { "name" : "Business applications", "level" : "intermediate" }, { "name" : "Data handling", "level" : "intermediate" }, { "name" : "Access controls", "level" : "intermediate" }, { "name" : "Prompt injection defenses", "level" : "intermediate" }, { "name" : "ITAR/export-control considerations", "level" : "intermediate" }, { "name" : "Runbooks", "level" : "intermediate" } ], "softSkills" : [ { "name" : "Ownership" }, { "name" : "Self-direct" } ], "majorSkills" : "AI Infrastructure, LLM applications, Agentic systems, RAG systems", "majorSkillsList" : [ "AI Infrastructure", "LLM applications", "Agentic systems", "RAG systems" ], "coreResponsibilities" : "Design AI-powered internal tools, Build AI-powered internal tools, Deploy AI-powered internal tools, Build LLM-powered applications, Build agents, Build RAG systems, Build intelligent workflow automations, Integrate with internal systems, Integrate with data sources, Partner with stakeholders, Identify AI tooling opportunities, Translate requirements into technical specs, Evaluate foundation models, Select frameworks, Build prompt evaluation, Build guardrails, Make build-versus-buy decisions, Develop AI engineering stack, Maintain AI engineering stack, Implement evaluation practices, Implement testing practices, Implement monitoring practices, Design integrations with internal systems, Design integrations with data telemetry, Design integrations with document stores, Design integrations with code repositories, Design integrations with business applications, Apply security practices to AI tooling, Apply compliance practices to AI tooling, Operate AI services in production, Produce technical documentation, Produce runbooks, Mentor team members on AI best practices, Raise the bar across the organization", "teamCollaboration" : "Work with engineers; Work with operators; Work with business stakeholders; Cross-functional teams; Internal tooling team", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Space transportation; Reusable launch systems; AI engineering; LLM; Agentic systems; RAG; Cloud-native architecture; ITAR; Export controls", "domainList" : [ "space-transportation", "reusable-launch-systems", "ai-engineering", "llm", "agentic-systems", "rag", "cloud-native-architecture", "itar", "export-controls" ], "domainSpecificKnowledge" : [ "Space transportation", "Reusable launch systems", "AI engineering", "LLM", "Agentic systems", "RAG", "Cloud-native architecture", "ITAR", "Export controls" ], "toolProficiency" : [ "Foundation models", "Vector stores", "Cloud platforms" ], "communicationSkills" : "Translate business problems", "documentationSkills" : "Technical documentation; Runbooks", "continuousLearning" : "Learn on the fly", "innovationCreativity" : "Identify high-leverage opportunities; Prototype development", "problemSolvingSkills" : "Root cause analysis; Troubleshooting; Translate fuzzy business problems", "specialRequirements" : "U. S. citizen or permanent resident, Eligible for export authorizations", "outcomesObjectives" : "Accelerate people building rockets; Meaningfully accelerate people building rockets; Remove friction; Unlock new capabilities; Ship AI tooling that works", "qualificationsBasic" : "Bachelor's or Master's degree in CS or related field, 5–8 years of experience, 2+ years building/shipping production AI/LLM systems, Proficiency in Python, TypeScript, or Go, Deep LLM tooling experience, Software engineering fundamentals, Experience integrating with enterprise systems, Understanding of AI security/privacy concerns, U. S. citizen or permanent resident", "qualificationsPreferred" : "Experience building agentic systems, Experience with vector databases, Experience deploying AI on AWS, Experience with model fine-tuning, Familiarity with ITAR/export controls", "workSiteFlexibility" : "Onsite", "rawDescription" : "At Stoke, we believe a thriving space economy will enable a vibrant, sustainable, and equitable future here on Earth. That is why we’re building Nova, our fully and rapidly reusable launch vehicle. Designed for daily flight, Nova tackles the core challenges of space transportation by reducing cost, increasing availability, and improving reliability. By radically lowering launch costs and increasing flight cadence, we’re helping create a truly scalable space industry. Our team is mission-driven, collaborative, and empowered to take ownership of their work. If you want to work alongside some of the most dedicated and talented people on Earth, we’d love to have you join us. Description Reusable launch systems are the key to seamlessly connecting Earth and space. Just as our rocket systems are designed to be reliable, automated, and intelligent, the internal tools that power our engineering and business operations must embody those same principles to help our teams move faster, work smarter, and stay focused on the mission. We are looking for a Senior AI Infrastructure Engineer to design, build, and deploy AI-powered tooling across Stoke’s internal systems. As part of our IT Internal Tooling team, you will identify high-leverage opportunities to apply AI - including large language models, agentic systems, retrieval pipelines, and intelligent automation - and turn them into production-grade tools that meaningfully accelerate the people building rockets. This role requires deep technical expertise in modern AI engineering, software development, and systems integration, combined with a strong product instinct for what to build, what not to build, and how to ship AI tooling that actually works. You will work closely with engineers, operators, and business stakeholders across Stoke to understand their workflows, identify where AI can remove friction or unlock new capabilities, and design and implement robust solutions end-to-end. This is a high-impact role where your work directly shapes how our company operates and how quickly our teams can deliver. You must be ready to stay focused, move quickly, self-direct, and learn on the fly. Responsibilities Design, develop, and deploy AI-powered internal tools end-to-end – from initial use-case discovery and prototyping through production deployment, monitoring, and iteration Build LLM-powered applications, agents, retrieval-augmented generation (RAG) systems, and intelligent workflow automations that integrate with Stoke’s internal systems and data sources Partner with stakeholders across engineering disciplines, manufacturing, supply chain, finance, and other teams to identify high-leverage opportunities for AI tooling and translate them into clear technical requirements Evaluate and select foundation models, frameworks, and platforms; build robust prompt, evaluation, and guardrail systems; and make pragmatic build-versus-buy decisions Develop and maintain the AI engineering stack used by the team, including model gateways, vector stores, evaluation harnesses, observability, and deployment pipelines Implement rigorous evaluation, testing, and monitoring practices for AI systems, including offline evals, online metrics, regression tracking, and human-in-the-loop review Design and implement integrations with internal systems and data including; telemetry data, systems requirements, document stores, code repositories, and business applications – using APIs, webhooks, and event-driven patterns Apply strong security, and compliance practices to AI tooling, including data handling, access controls, prompt injection defenses, and ITAR/export-control considerations Operate AI services in production, including capacity planning, cost optimization, latency tuning, and incident response Produce clear technical documentation, runbooks, and architectural decision records; mentor team members on applied AI best practices and help raise the bar across the organization Qualifications Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience Combined 5–8 years of experience in software engineering, applied AI/ML, or related roles, with at least 2 years building and shipping production AI or LLM-powered systems Proven track record of designing, deploying, and operating AI-powered applications at scale in a production environment Strong proficiency in at least one modern language commonly used in AI tooling (e.g., Python, TypeScript, Go) Deep, hands-on experience with modern LLM tooling and patterns, including prompt engineering, function/tool calling, agents, RAG, and structured output Working knowledge of one or more major foundation model providers (e.g., Anthropic, OpenAI, AWS Bedrock, Azure OpenAI) and the trade-offs between them Strong software engineering fundamentals: testing, code review, CI/CD, version control, observability, and clean API design Experience integrating with enterprise systems via REST APIs, webhooks, message queues, and event-driven architectures Solid understanding of evaluation methodologies for AI systems, including offline evals, golden datasets, and online quality metrics Strong understanding of AI security and privacy concerns, including data leakage, prompt injection, model misuse, and least-privilege data access Excellent communication skills and the ability to translate fuzzy business problems into concrete, shippable AI solutions Preferred Qualifications Experience building agentic systems with multi-step tool use, planning, and long-running workflows Experience with vector databases, embedding models, hybrid search, and advanced retrieval techniques Experience deploying AI workloads on AWS (Bedrock, Lambda, ECS/Fargate) or comparable cloud platforms Experience with model fine-tuning, distillation, or training custom models for narrow internal use cases Familiarity with ITAR, export controls, or other regulated-data environments and the implications for AI tooling Experience with MCP (Model Context Protocol) servers, internal developer platforms, or building reusable AI infrastructure for other engineers Background in IT, internal tools, or digital transformation functions, with a track record of successful enterprise software rollouts Passion for learning new technologies and sharing knowledge with teammates Benefits Equity – We know that our employees are the reason we succeed. To give everyone a stake in our future, we are pleased to offer equity in the form of stock options to all regular, full-time employees. Comprehensive benefits program including subsidized medical, dental, and vision insurance Company-paid life and disability insurance 401(k) plan with employer match 4 weeks’ Paid Time Off Holidays – 10 days (including an end-of-year closure) Paid Family/Parental Leave On-site gym or monthly wellness stipend (depending on location) Dog friendly offices! Compensation Target Levels: Level 4 Range: $192,885 - $289,380 Level 5 Range: $231,525 - $347,235 Our job posts are intentionally written to attract a wide variety of experience levels, and we make decisions about the right fit on a per-candidate basis. Your actual level and base salary will be decided based on your specific experience and skill level. ITAR Requirements To conform to U. S. Government space technology export regulations, including the International Traffic in Arms Regulations (ITAR), you must be a U. S. citizen, lawful permanent resident of the U.S., protected individual as defined by 8 U.S. C. 1324b(a)(3), or eligible to obtain the required authorizations from the U. S. Department of State. Equal Opportunity The Company is an Equal Opportunity Employer, including with respect to disability and veteran status. It is committed to compliance with all equal opportunity laws, including the Immigration and Nationality Act (INA) and Title VII. It does not discriminate on the basis of nationality, race, citizenship, immigration status, or any other protected class when it comes to employment practices, including hiring. Employment at the Company is contingent upon satisfactory completion of reference and background checks, and on your ability to prove your identity and authorization to work in the U. S. for the Company. Employees must comply with the United States Citizenship and Immigration Services employment verification requirements, and, therefore, they must complete an Employment Eligibility Verification Form I-9 at the start of employment and re-verify authorization to work periodically. Separate from this I-9 process, this position entails access to certain technology and technical data that is restricted under U. S. export control laws and regulations. Employment or continued employment may be conditioned on your legal authorization to work with or have access to export control materials as necessary to perform your job. Candidate Rights & Accommodations If you require a reasonable accommodation to complete the application or participate in the interview process, please contact careers@stokespace.com. Requests will be handled in accordance with applicable laws. Please do not include medical or other confidential information in your initial request. For more information about your rights, please refer to the \"Know Your Rights\" notice here. E-Verify Stoke Space uses E-Verify to confirm the identity and employment eligibility of all new hires.", "summaryDescription" : "Senior AI Infrastructure Engineer at Stoke Space. Skills: AI Infrastructure, LLM applications, Agentic systems, RAG systems. Design AI-powered internal tools. Build AI-powered internal tools", "postedDate" : "2026-06-11T21:10:42.177", "createdAt" : "2026-06-11T21:10:42.177", "lastUpdated" : "2026-06-14T22:16:06.716", "ingestTimestamp" : "2026-06-11T21:10:42.177", "mongoId" : "6a2a54ec74d8ee00a06052fc", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 165000, "salaryAnnualMax" : 235000, "salaryBand" : "150k-200k", "hasSalary" : true, "allSkills" : [ "AI engineering", "Software development", "Intelligent automation", "Model gateways", "Vector stores", "Evaluation harnesses", "Observability", "Deployment pipelines", "Offline evals", "Online metrics", "Regression tracking", "Human-in-the-loop review", "Data telemetry", "Document stores", "Code repositories", "Business applications", "Data handling", "Access controls", "Prompt injection defenses", "ITAR/export-control considerations", "Runbooks", "Ownership", "Self-direct", "AI Infrastructure", "LLM applications", "Agentic systems", "RAG systems", "Product instinct", "Systems integration", "Prompt engineering", "Evaluation methodologies", "Capacity planning", "Cost optimization", "Latency tuning", "Incident response", "Architectural decision making", "Roadmap planning", "Space transportation", "Reusable launch systems", "LLM", "RAG", "Cloud-native architecture", "ITAR", "Export controls", "Foundation models", "Cloud platforms" ], "skillCount" : 46, "jobCategory" : "other", "jobSubcategory" : "software", "dataQualityScore" : 0.8888889, "_score" : 608.36365, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a305117f292fd229cef954d", "title" : "Agentic Solution Engineer", "industry" : "IT", "salary" : { "min" : 2500000.0, "max" : 4500000.0, "currency" : "INR", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Senior Agentic Solution Engineer in India, adjusted for the technology industry and onsite work mode." }, "location" : "India", "locations" : [ "India" ], "timestamp" : "2026-06-16T11:53:12.454", "fingerprint" : "b890a160b20b30494d984864d395a59a104ec62ad013678a6d7a0a9f4fbc0ede", "source" : "lever", "language" : "en", "applyUrl" : "https://jobs.lever.co/jobgether/30b5423a-080f-472f-9d52-4f4f250142d5/apply", "externalId" : "30b5423a-080f-472f-9d52-4f4f250142d5", "industryFunction" : { }, "structuredLocations" : [ { "country" : "India", "continent" : "as", "workMode" : "onsite" } ], "locationText" : "India", "employmentType" : "FULL_TIME", "experienceMinYears" : 5, "experienceMaxYears" : 7, "experienceLevel" : "Senior", "technicalSkills" : "LLM-powered agents, REST APIs, Webhooks, JSON, No-code/low-code platforms, AI agents", "professionalSkills" : [ "System design", "Fault-tolerant system design" ], "hardSkillsList" : [ "Prompt engineering", "API integration", "Data transformation", "Error handling", "System resilience" ], "hardSkills" : [ { "name" : "Prompt engineering", "level" : "intermediate" }, { "name" : "API integration", "level" : "intermediate" }, { "name" : "Data transformation", "level" : "intermediate" }, { "name" : "Error handling", "level" : "intermediate" }, { "name" : "System resilience", "level" : "intermediate" } ], "majorSkills" : "Prompt engineering, Agentic workflows, API integration, LLM", "majorSkillsList" : [ "Prompt engineering", "Agentic workflows", "API integration", "LLM" ], "coreResponsibilities" : "Design high-quality prompts for LLM-powered agents, Develop high-quality prompts for LLM-powered agents, Build agentic workflows, Configure agentic workflows, Integrate internal APIs, Integrate external APIs, Manage authentication, Manage data transformation, Manage robust error handling, Implement testing strategies, Debug issues, Ensure end-to-end reliability of agent workflows, Optimize AI agents for performance, Optimize AI agents for scalability, Optimize AI agents for operational cost, Optimize AI agents for system resilience, Collaborate with cross-functional teams, Translate requirements into scalable solutions, Translate requirements into production-ready AI solutions, Support continuous improvement of agent systems, Refine agent systems, Enhance agent systems", "teamCollaboration" : "Cross-functional teams", "domainKnowledge" : "Agentic AI; Enterprise automation; Large language models; Distributed application design", "domainList" : [ "agentic-ai", "enterprise-automation", "large-language-models", "distributed-application-design" ], "domainSpecificKnowledge" : [ "Agentic AI", "Enterprise automation", "Large language models", "Distributed application design" ], "continuousLearning" : "AI systems; Distributed architecture; Automation tooling", "problemSolvingSkills" : "Troubleshooting", "qualificationsBasic" : "5–7 years of experience as a Software Engineer, Understanding of prompt engineering, Understanding of behavior of large language models (LLMs), Hands-on experience with REST APIs, Hands-on experience with webhooks, Hands-on experience with JSON-based integrations, Hands-on experience with system-to-system communication, Solid experience in debugging, Solid experience in unit testing, Solid experience in troubleshooting production-grade applications, Knowledge of resilient system design principles, Knowledge of failure handling, Knowledge of non-happy-path scenarios, Ability to work closely with customers, Ability to work closely with stakeholders, Translate business requirements into technical solutions", "qualificationsPreferred" : "Experience with workflow automation, Experience with integration systems, Experience with distributed application design, Exposure to observability, Exposure to monitoring, Exposure to production system analytics, Familiarity with no-code/low-code platforms, Familiarity with agentic AI systems", "remoteFriendly" : true, "workSiteFlexibility" : "Remote", "rawDescription" : "## Accountabilities Design and develop high-quality prompts for LLM-powered agents, ensuring accuracy, reliability, and contextual performance. Build and configure agentic workflows using a no-code/low-code automation platform for enterprise-scale use cases. Integrate internal and external APIs, managing authentication, data transformation, and robust error handling. Implement testing strategies, debug issues, and ensure end-to-end reliability of agent workflows in production environments. Apply software engineering best practices including retries, idempotency, timeouts, and fault-tolerant system design. Optimize AI agents for performance, scalability, operational cost, and system resilience. Collaborate with cross-functional teams to translate requirements into scalable, production-ready AI solutions. Support continuous improvement of agent systems through monitoring, refinement, and iterative enhancement. Requirements: 5–7 years of experience as a Software Engineer or similar technical role in enterprise or product environments. Strong understanding of prompt engineering and behavior of large language models (LLMs). Hands-on experience with REST APIs, webhooks, JSON-based integrations, and system-to-system communication. Solid experience in debugging, unit testing, and troubleshooting production-grade applications. Strong knowledge of resilient system design principles, including failure handling and non-happy-path scenarios. Ability to work closely with customers and stakeholders to translate business requirements into technical solutions. Experience with workflow automation, integration systems, or distributed application design is highly desirable. Exposure to observability, monitoring, or production system analytics is a plus. Familiarity with no-code/low-code platforms and agentic AI systems is an advantage. Benefits: Opportunity to work at the forefront of agentic AI and enterprise automation technologies. High-impact role building AI systems used by global enterprise customers. Exposure to cutting-edge LLM-based workflows, prompt engineering, and AI orchestration platforms. Collaborative, innovation-driven environment with strong engineering and product partnership. Competitive compensation and performance-based growth opportunities. Flexible work culture supporting autonomy and work-life balance. Continuous learning opportunities in AI systems, distributed architecture, and automation tooling. ## Additional Information How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1", "summaryDescription" : "Agentic Solution Engineer. Skills: Prompt engineering, Agentic workflows, API integration, LLM. Design high-quality prompts for LLM-powered agents. 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"title" : "Engineer, Enterprise Service Desk", "company" : "ABACUS", "industry" : "Technology", "salary" : { "min" : 82000.0, "max" : 92000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : false }, "location" : "Atlanta, Georgia, United States", "locations" : [ "Atlanta", "Georgia", "United States", "Charlotte", "North Carolina", "United States", "Columbus", "Ohio", "United States", "Fort Lauderdale", "Florida", "United States", "Newark", "New Jersey", "United States", "Orlando", "Florida", "United States" ], "certifications" : [ "MCSA: Server Infrastructure", "MCSA: O365" ], "timestamp" : "2026-06-15T09:06:33.436", "fingerprint" : "c1e049bed7d376801f08f487bb6e319e0b1368a04459012368b6f5c7d61c9848", "source" : "greenhouse", "language" : "en", "applyUrl" : "https://abacustechnology.com/about/careers/current-vacancies/?gh_jid=7746432003", "externalId" : "7746432003", "industryFunction" : { }, "structuredLocations" : [ { "city" : "Atlanta", "state" : "Georgia", "country" : 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"Telephony systems", "Virtual environments", "High Availability", "Security posture" ], "communicationSkills" : "Client communication; Verbal communication; Written communication", "documentationSkills" : "Create documentation; Maintain documentation", "continuousLearning" : "Learn new technology skills; Retain new technology skills", "problemSolvingSkills" : "Problem solving; Troubleshooting processes; Resolve issues; Troubleshoot emergencies", "specialRequirements" : "Commute to office", "outcomesObjectives" : "Provide world class client experience; Resolve complex issues; Resolve client emergencies; Perform restore testing; Continue customer satisfaction", "qualificationsBasic" : "5+ years Systems Engineer, MCSA: Server Infrastructure, MCSA: O365, Windows 2016/2012/2008 servers, Active Directory, SQL, SharePoint, Exchange Servers, Backup Technologies, Internet/DNS/E-mail/Communication issues, VMWare, Citrix, VPN, Terminal Services, VoIP, Voicemail, Analog hardware/software, Vendor 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In addition to leading projects, Level Threes provide escalation support to all service delivery team members. Responsibilities (including, but not limited to): Deliver an excellent customer experience in all interactions Resolve new and escalated service tickets, provide guidance for or personally resolve aging and complex issues Assist clients with the design and implementation, installation, configuration and ongoing usability of desktop computers, mobile devices, peripheral equipment, telephony systems, servers, storage, networking and software Troubleshoot and resolve client emergencies with minimal oversight, persevering until resolved Work with vendor representatives to resolve software and hardware issues Install and/or upgrade Microsoft Server Operating Systems Perform advanced virus, malware and ransomware mediation Provide professional quality server room cable management Responsible for creating and maintaining high quality, detailed documentation Resolve complex backup issues and perform restore testing Notifies Client Success Managers when outdated equipment causes repeated issues Install, configure, support complex virtual environments with High Availability in VMWare ESXi and Hyper-V environments Work with clients to harden security posture through policy and advanced technologies according to Abacus standards and processes Communicate with clients as required: Keeping them informed of incident progress, notifying them of impending changes or agreed upon outages Accountable for continued customer satisfaction and coordinates all activities with the client, assists with client training while representing Abacus in a professional manner Exhibit adaptability and is willing to alter shifts and job requirements to meet the needs of clients and Abacus Comply with all safety requirements, including but not limited to: completing all required training, following all guidance provided in Abacus policies, procedures, field guidelines, reporting requirements, and technical advisories. Demonstrates a pro-active approach toward safety, health, and quality in compliance with all Company, governmental and customer requirements Lead teams on large, complex projects (i. e. system migrations, virtual server configurations with high availability, server and firewall installations, VPN tunnel configurations, SAN setups, etc.) Participate in project planning, solution delivery, mentoring and teaching improved processes to team members Serve as an escalation point to mentor all team members Prepare and deliver staff training material to advance the skills of the technical team Follow Abacus's defined processes, policies, service delivery standards All other duties assigned Qualifications and Education Requirements: Associates degree in technology related field OR equivalent combination of education and work experience A minimum of 5+ years of as a Systems Engineer or similar role, working in Microsoft Environments Required certifications: MCSA: Server Infrastructure (70-410, 70-411, 70-412) or equivalent, MCSA: O365 (MS-100, MS-101), business and leadership experience Strong understanding of Windows 2016/2012/2008 servers, Active Directory, SQL, SharePoint, Exchange Servers, Backup Technologies, Internet/DNS/E-mail/Communication issues Strong working knowledge of VMWare, Citrix, VPN and Terminal Services Strong working knowledge of VoIP, voicemail, analog, and vendor specific hardware/software Excellent problem solving and client relationship skills Excellent verbal and written communication skills Ability to learn and retain new technology skills and troubleshooting processes, team player ,maintain calm and present yourself professionally in high stress situations MSP specific experience strongly desired Ability to commute to office on a hybrid basis Salary DOE: $82k-$92k", "summaryDescription" : "Engineer, Enterprise Service Desk at ABACUS. 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mediation, Perform ransomware mediation, Provide server room cable management, Create documentation, Maintain documentation, Resolve backup issues, Perform restore testing, Notify Client Success Managers, Install virtual environments, Configure virtual environments, Support virtual environments, Harden security posture, Communicate with clients, Inform clients of incident progress, Notify clients of changes, Notify clients of outages, Coordinate activities with client, Assist with client training, Comply with safety requirements, Complete required training, Follow MIT policies, Follow MIT procedures, Follow MIT field guidelines, Follow MIT reporting requirements, Follow MIT technical advisories, Demonstrate pro-active safety approach, Demonstrate pro-active health approach, Demonstrate pro-active quality approach, Lead teams on complex projects, Participate in project planning, Participate in solution delivery, Mentor team members, Teach improved processes, Serve as escalation point, 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Citrix, VPN, Terminal Services, VoIP, Voicemail, Analog hardware/software, Vendor specific hardware/software", "qualificationsPreferred" : "MSP specific experience", "remoteFriendly" : true, "workSiteFlexibility" : "Hybrid", "rawDescription" : "Job Summary: Abacus’s Engineer, Enterprise Service Desk role is responsible for the design and implementation of customer facing and internal systems, including public and private cloud environments as well as on premise infrastructure and telephony systems, all while providing a world class client experience daily. 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Responsibilities (including, but not limited to): Deliver an excellent customer experience in all interactions Resolve new and escalated service tickets, provide guidance for or personally resolve aging and complex issues Assist clients with the design and implementation, installation, configuration and ongoing usability of desktop computers, mobile devices, peripheral equipment, telephony systems, servers, storage, networking and software Troubleshoot and resolve client emergencies with minimal oversight, persevering until resolved Work with vendor representatives to resolve software and hardware issues Install and/or upgrade Microsoft Server Operating Systems Perform advanced virus, malware and ransomware mediation Provide professional quality server room cable management Responsible for creating and maintaining high quality, detailed documentation Resolve complex backup issues and perform restore testing Notifies Client Success Managers when outdated equipment causes repeated issues Install, configure, support complex virtual environments with High Availability in VMWare ESXi and Hyper-V environments Work with clients to harden security posture through policy and advanced technologies according to Abacus standards and processes Communicate with clients as required: Keeping them informed of incident progress, notifying them of impending changes or agreed upon outages Accountable for continued customer satisfaction and coordinates all activities with the client, assists with client training while representing MIT in a professional manner Exhibit adaptability and is willing to alter shifts and job requirements to meet the needs of clients and Abacus Comply with all safety requirements, including but not limited to: completing all required training, following all guidance provided in MIT policies, procedures, field guidelines, reporting requirements, and technical advisories. Demonstrates a pro-active approach toward safety, health, and quality in compliance with all Company, governmental and customer requirements Lead teams on large, complex projects (i. e. system migrations, virtual server configurations with high availability, server and firewall installations, VPN tunnel configurations, SAN setups, etc.) Participate in project planning, solution delivery, mentoring and teaching improved processes to team members Serve as an escalation point to mentor all team members Prepare and deliver staff training material to advance the skills of the technical team Follow Abacus's defined processes, policies, service delivery standards All other duties assigned Qualifications and Education Requirements: Associates degree in technology related field OR equivalent combination of education and work experience A minimum of 5+ years of as a Systems Engineer or similar role, working in Microsoft Environments Required certifications: MCSA: Server Infrastructure (70-410, 70-411, 70-412) or equivalent, MCSA: O365 (MS-100, MS-101), business and leadership experience Strong understanding of Windows 2016/2012/2008 servers, Active Directory, SQL, SharePoint, Exchange Servers, Backup Technologies, Internet/DNS/E-mail/Communication issues Strong working knowledge of VMWare, Citrix, VPN and Terminal Services Strong working knowledge of VoIP, voicemail, analog, and vendor specific hardware/software Excellent problem solving and client relationship skills Excellent verbal and written communication skills Ability to learn and retain new technology skills and troubleshooting processes, team player ,maintain calm and present yourself professionally in high stress situations MSP specific experience strongly desired Ability to commute to office on a hybrid basis", "summaryDescription" : "Engineer, Enterprise Service Desk at ABACUS. 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Partner with engineering teams; Collaborate with enterprise architecture", "projectManagementSkills" : [ "Roadmap planning" ], "domainKnowledge" : "Insurance; Financial services; Regulated industries; Cloud; Integration; Data; AI; Observability; Agentic patterns; Model lifecycles; Human-in-the-loop; Safety; Compliance", "domainList" : [ "insurance", "financial-services", "regulated-industries", "cloud", "integration", "data", "ai", "observability", "agentic-patterns", "model-lifecycles", "human-in-the-loop", "safety", "compliance" ], "domainSpecificKnowledge" : [ "Insurance", "Financial services", "Regulated industries", "Cloud", "Integration", "Data", "AI", "Observability", "Agentic patterns", "Model lifecycles", "Human-in-the-loop", "Safety", "Compliance" ], "innovationCreativity" : "Innovate quickly", "problemSolvingSkills" : "Solve real business problems", "outcomesObjectives" : "Accelerate product delivery; Improve engineering effectiveness; Innovate quickly; Drastically reduce technical debt; Improve agentic automation; Improved velocity; Achieve widespread organizational adoption; Track platform consumption; Track platform performance; Track business value delivered", "qualificationsBasic" : "20+ years enterprise technology leadership, 10+ years platform strategy, 10+ years product management, Deep understanding of Cloud, Deep understanding of Integration/API strategies, Deep understanding of Ingestion, Deep understanding of Data, Deep understanding of AI, Deep understanding of Observability, Translate technical strategies to outcomes, Achieve widespread organizational adoption", "qualificationsPreferred" : "Experience in insurance, Experience in financial services, Experience in regulated industries, Background in cloud engineering, Background in data engineering, Background in software engineering, Background in enterprise architecture, BS in Computer Science, BS in Engineering, Equivalent degree", "remoteFriendly" : false, "workSiteFlexibility" : "Onsite", "rawDescription" : "VP IT Management - IM04AE We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. The Vice President of Enterprise Platform Strategy and Activation is responsible for defining, building, and scaling enterprise platforms, tools, and capabilities that accelerate product delivery and engineering effectiveness. This executive ensures teams have the right platforms, patterns, automation, AI and shared services to innovate quickly. The role leads the multi-year strategy and operating model for the company’s foundational platforms spanning cloud, application, integration, engineering experience, and platform observability. **Key Responsibilities** * Define the long-term strategic roadmap for enterprise platforms, with a focus on emerging technologies. Spearhead our shift toward **AI-first principles** , integrating agentic patterns, model lifecycles, and human-in-the-loop guardrails into the fabric of our platforms. * Own the vision, lifecycle, and roadmap for core platforms, including cloud, engineering productivity, integration and ingestion platforms, API ecosystems, and automation capabilities. * Implement best-in-class platform engineering practices designed to drastically reduce technical debt, improve agentic automation, resulting in improved velocity. * Partner deeply with CIOs and engineering teams to understand their unique needs, ensuring high adoption rates of platform capabilities by solving real business problems. * Collaborate with enterprise architecture functions to ensure all designed platforms are scalable, secure, highly interoperable, and aligned with broader business goals. * Establish and monitor clear KPIs and maturity metrics to track platform consumption, performance, and business value delivered. * Prioritize platform investments and portfolio via value-based roadmaps, balancing modernization, innovation, and regulatory obligations. * Drive AI-first principles into platforms (agentic patterns, model lifecycle, guardrails, human-in-the-loop, safety & compliance). **Qualifications** **Required:** * Executive Experience: 20+ years of distinguished experience in enterprise technology leadership, with at least 10+ years dedicated to platform strategy or product management within large, complex, and regulated organizations. * Proven Transformation: Demonstrated success in leading enterprise-scale platform initiatives. You have a deep understanding of Cloud, Integration/API strategies, Ingestion, Data, AI, and Observability. * Outcome-Oriented: A proven track record of translating complex technical strategies into measurable business outcomes and achieving widespread organizational adoption. **Preferred:** * Experience in insurance/financial services or similarly regulated industries. * Background in cloud/data/software engineering, enterprise architecture. * BS in Computer Science/Engineering, or equivalent. **Compensation** The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is: $222,480 - $333,720 Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age [About Us](https://www.thehartford.com/about-us) | [Our Culture](https://www.thehartford.com/about-us/corporate-culture) | [What It’s Like to Work Here](https://www.thehartford.com/careers/our-employees) | [Perks & Benefits](https://www.thehartford.com/careers/benefits)", "summaryDescription" : "VP, Enterprise Platform Strategy and Activation at The Hartford. Skills: Enterprise platforms, Platform strategy, AI-first principles. Define strategic roadmap for enterprise platforms. Integrate agentic patterns", "postedDate" : "2026-06-11T13:08:31.387", "createdAt" : "2026-06-11T13:08:30.469", "lastUpdated" : "2026-06-12T17:53:02.150", "ingestTimestamp" : "2026-06-11T13:08:30.469", "mongoId" : "6a2a40aa74d8ee00a05c83f5", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "sourceUrl" : "https://thehartford.wd5.myworkdayjobs.com/Careers_Restricted/job/Hartford-CT/VP--Enterprise-Platform-Strategy-and-Activation_R2625663", "salaryAnnualMin" : 222480, "salaryAnnualMax" : 333720, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Platform engineering", "Agentic automation", "Enterprise platforms", "Platform strategy", "AI-first principles", "Product management", "Enterprise architecture", "Value-based roadmaps", "Regulatory obligations", "Roadmap planning", "Insurance", "Financial services", "Regulated industries", "Cloud", "Integration", "Data", "AI", "Observability", "Agentic patterns", "Model lifecycles", "Human-in-the-loop", "Safety", "Compliance" ], "skillCount" : 23, "jobCategory" : "other", "seniorityLevel" : "executive", "dataQualityScore" : 1.0, "_score" : 606.1522, "daysOld" : 1, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Insurance" }, { "id" : "6a2a8ef374d8ee00a068816a", "title" : "Founding Engineer: Enterprise Integrations", "industry" : "Engineering", "salary" : { "min" : 220000.0, "max" : 300000.0, "currency" : "USD", "frequency" : "yearly", "is_estimated" : true, "estimation_basis" : "Market baseline for a Lead Founding Engineer in San Francisco, adjusted for senior experience and the technology industry." }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-14T22:24:28.730", "fingerprint" : "755a541899ed4a7a90bb1b19d850669b2ee16216d9eeea2fed0ca0944aac6afa", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/Clera/9bee13f0-2d02-46c4-8230-d7502f26e7de/application", "externalId" : "9bee13f0-2d02-46c4-8230-d7502f26e7de", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "experienceMinYears" : 3, "experienceMaxYears" : 10, "experienceLevel" : "Senior", "technicalSkills" : "TypeScript, React, Node.js, AWS, PostgreSQL", "professionalSkills" : [ "System design", "Technical leadership" ], "hardSkillsList" : [ "End-to-end development", "Distributed systems" ], "hardSkills" : [ { "name" : "End-to-end development", "level" : "intermediate" }, { "name" : "Distributed systems", "level" : "intermediate" } ], "majorSkills" : "Enterprise Integrations, Agent platform, Infrastructure", "majorSkillsList" : [ "Enterprise Integrations", "Agent platform", "Infrastructure" ], "coreResponsibilities" : "Own core systems, Own agent platform, Own infrastructure, Own integrations runtime, Set engineering patterns, Ship to production, Deliver reliable systems, Deliver observable systems", "teamCollaboration" : "Work with founders", "domainKnowledge" : "Agent-based platforms; Distributed systems", "domainList" : [ "agent-based-platforms", "distributed-systems" ], "domainSpecificKnowledge" : [ "Agent-based platforms", "Distributed systems" ], "outcomesObjectives" : "Measurable customer impact", "qualificationsBasic" : "3+ years software engineering experience, Build something 0 to 1, TypeScript proficiency, React proficiency, Node.js proficiency, LLM integration experience, Agent-based platform experience, AWS experience, PostgreSQL experience, End-to-end feature development, Observability experience, Monitoring experience, Tracing experience, Retry patterns experience, Queuing patterns experience", "qualificationsPreferred" : "Startup experience preferred", "rawDescription" : "ABOUT THE ROLE We're looking for our first engineering hire to own core systems end-to-end and help set the patterns that will shape the team as we scale. You'll work closely with the founders to ship production-ready systems for an agentic integration platform used by paying enterprise customers. WHAT YOU'LL DO - Own core systems end-to-end: agent platform, infrastructure, and the integrations runtime. - Set the engineering patterns that every future hire will build on. - Work directly with the founders, providing opinion and technical leadership. - Ship to production constantly, delivering reliable, observable systems. WHAT WE'RE LOOKING FOR - 3+ years of software engineering experience in fast-paced environments (startup experience preferred). - Proven ability to build something 0 to 1, in early-stage startups or serious side projects. - Proficiency in TypeScript and React for frontend; Node.js for backend. - Experience integrating or building workflows around large language models (LLMs) and agent-based platforms. - Experience with AWS and PostgreSQL for cloud and data storage. - Experience owning end-to-end feature development across frontend, backend, and infra with measurable customer impact. - Experience with observability, monitoring, tracing, and reliable retry/queuing patterns in distributed systems.", "summaryDescription" : "Founding Engineer: Enterprise Integrations. Skills: Enterprise Integrations, Agent platform, Infrastructure. Own core systems. Own agent platform", "postedDate" : "2026-06-11T18:41:14.619", "createdAt" : "2026-06-11T18:41:14.619", "lastUpdated" : "2026-06-14T22:24:28.730", "ingestTimestamp" : "2026-06-11T18:41:14.619", "mongoId" : "6a2a8ef374d8ee00a068816a", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 220000, "salaryAnnualMax" : 300000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "End-to-end development", "Distributed systems", "Enterprise Integrations", "Agent platform", "Infrastructure", "System design", "Technical leadership", "Agent-based platforms" ], "skillCount" : 8, "jobCategory" : "engineering", "jobSubcategory" : "engineering", "dataQualityScore" : 0.8888889, "_score" : 605.65125, "daysOld" : 3, "hasLocation" : true, "hasGeo" : true }, { "id" : "6a2cb02174d8ee00a09d8fa4", "title" : "Agentic Risk Analyst", "company" : "OpenAI", "industry" : "Intelligence & Investigations", "salary" : { "min" : 288000.0, "max" : 425000.0, "currency" : "USD", "frequency" : "Yearly" }, "location" : "San Francisco", "locations" : [ "San Francisco" ], "timestamp" : "2026-06-15T12:06:15.923", "fingerprint" : "2010f352b63933dee90bc3ff91961f06084c61e70b936ec1806cd827a047e05c", "source" : "ashby", "language" : "en", "applyUrl" : "https://jobs.ashbyhq.com/OpenAI/e4d0e517-4380-43f3-b5ee-1ce30a88539f/application", "externalId" : "e4d0e517-4380-43f3-b5ee-1ce30a88539f", "industryFunction" : { }, "structuredLocations" : [ { "city" : "San Francisco", "state" : "California", "country" : "United States", "continent" : "na", "source" : "llm", "workMode" : "onsite", "geo" : "37.7879363,-122.4075201" } ], "locationText" : "San Francisco, California, United States", "employmentType" : "FULL_TIME", "technicalSkills" : "AI, ML, DevOps, Cloud, Data Engineering, Security", "professionalSkills" : [ "Risk analysis", "Strategic perspective", "System-level perspective", "Adversarial misuse", "Unintended behavior", "Risk prioritization", "Mitigation strategy", "Forecasting", "Scenario work", "Decision making", "Coordination", "Product decisions", "Safety mitigations", "Governance" ], "hardSkillsList" : [ "Risk assessment", "Threat analysis", "Data synthesis", "Signal analysis", "Impact assessment", "Severity assessment", "Evidence assessment", "Uncertainty assessment", "Priority assessment", "Action recommendation", "Launch readiness", "Risk escalation", "Risk tracking", "Horizon scanning", "Failure mode analysis", "Control gap analysis", "Harm analysis", "Stakeholder communication", "Metric definition", "Metric tracking", "Risk indicators", "Monitoring capabilities" ], "hardSkills" : [ { "name" : "Risk assessment", "level" : "intermediate" }, { "name" : "Threat analysis", "level" : "intermediate" }, { "name" : "Data synthesis", "level" : "intermediate" }, { "name" : "Signal analysis", "level" : "intermediate" }, { "name" : "Impact assessment", "level" : "intermediate" }, { "name" : "Severity assessment", "level" : "intermediate" }, { "name" : "Evidence assessment", "level" : "intermediate" }, { "name" : "Uncertainty assessment", "level" : "intermediate" }, { "name" : "Priority assessment", "level" : "intermediate" }, { "name" : "Action recommendation", "level" : "intermediate" }, { "name" : "Launch readiness", "level" : "intermediate" }, { "name" : "Risk escalation", "level" : "intermediate" }, { "name" : "Risk tracking", "level" : "intermediate" }, { "name" : "Horizon scanning", "level" : "intermediate" }, { "name" : "Failure mode analysis", "level" : "intermediate" }, { "name" : "Control gap analysis", "level" : "intermediate" }, { "name" : "Harm analysis", "level" : "intermediate" }, { "name" : "Stakeholder communication", "level" : "intermediate" }, { "name" : "Metric definition", "level" : "intermediate" }, { "name" : "Metric tracking", "level" : "intermediate" }, { "name" : "Risk indicators", "level" : "intermediate" }, { "name" : "Monitoring capabilities", "level" : "intermediate" } ], "majorSkills" : "Agentic risk, Risk analysis, Threat intelligence", "majorSkillsList" : [ "Agentic risk", "Risk analysis", "Threat intelligence" ], "coreResponsibilities" : "Build and maintain risk portfolio, Map risks to workstreams, Run intake and review cadence, Identify emerging risks, Route findings to owners, Connect incidents to trends, Produce clear assessments, Assess capability impact, Surface unowned risks, Track residual risk, Use external developments, Apply frameworks for failure modes, Communicate findings to stakeholders, Define operating metrics, Track program metrics, Partner on evaluations", "teamCollaboration" : "Cross-functional teams; Product teams; Safety teams; Security teams; Policy teams; Governance teams; Measurement experts; Forecasting experts; Investigators; Engineers", "domainKnowledge" : "Agentic systems; AI safety; AI security; Adversarial activity; Emerging technologies; Autonomy; Multi-step task execution; Tool use; Memory; Retrieval; Connectors; Computer-use capabilities; Multi-agent workflows", "domainList" : [ "agentic-systems", "ai-safety", "ai-security", "adversarial-activity", "emerging-technologies", "autonomy", "multi-step-task-execution", "tool-use", "memory", "retrieval", "connectors", "computer-use-capabilities", "multi-agent-workflows" ], "domainSpecificKnowledge" : [ "Agentic systems", "AI safety", "AI security", "Adversarial activity", "Emerging technologies", "Autonomy", "Multi-step task execution", "Tool use", "Memory", "Retrieval", "Connectors", "Computer-use capabilities", "Multi-agent workflows" ], "communicationSkills" : "Decision-ready assessments", "problemSolvingSkills" : "Root cause analysis; Troubleshooting", "qualificationsBasic" : "Company-wide portfolio of risks, Cross-functional intake and review cadence, Assess emerging capabilities and product changes, Apply practical frameworks and taxonomies, Produce concise, decision-ready assessments, Define and track operating metrics, Partner with colleagues on evaluations", "remoteFriendly" : true, "workSiteFlexibility" : "Onsite", "rawDescription" : "ABOUT THE TEAM The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors. ABOUT THE ROLE As an Agentic Risk Analyst, you will shape OpenAI’s operating picture for current agentic risk across products and platforms. You will bring a strategic, system-level perspective to current risks, connecting individual incidents, technical findings, abuse patterns, and external developments to relevant workstreams, mitigations, owners, dependencies, and residual gaps. You will analyze how risks emerge through autonomy, multi-step task execution, tool use, memory, retrieval, connectors, computer-use capabilities, and multi-agent workflows, with a particular focus on both adversarial misuse and unintended system behavior. By synthesizing signals from investigations, evaluations, red teaming, security reviews, product launches, external research, and real-world incidents, you will maintain a current view of material risks and evolving threat patterns. Your work will help turn complex and often ambiguous signals into coordinated decisions and measurable follow-through across product, safety, security, policy, and governance teams. You will work closely with investigators, engineers, product, policy, safety, and security teams, and measurement and forecasting experts who lead longer-horizon risk discovery and scenario work to maintain a shared operating picture of current risks, mitigation priorities, owners, and dependencies. This is an opportunity to help shape how OpenAI coordinates decisions and follow-through across the evolving risk landscape of increasingly capable agentic systems, ensuring that safety decisions keep pace with rapidly advancing technology. IN THIS ROLE, YOU WILL: - Build and maintain a current, company-wide portfolio of material agentic risks across OpenAI’s products, platforms, and emerging capabilities, mapping each risk to relevant workstreams, owners, mitigations, dependencies, decisions, and residual gaps. - Run a cross-functional intake and review cadence for signals from across OpenAI and the broader ecosystem to identify emerging risks, evolving threat patterns, and important shifts in the agentic risk landscape, routing findings to the right owners and decision-makers - Connect individual incidents, technical findings, evaluations, and weak signals to broader system-level trends, producing clear assessments of impact, severity, evidence, uncertainty, priority, and recommended action. - Assess how emerging capabilities, product changes, ecosystem developments, and adversary adaptation may affect current risk priorities and launch readiness, surfacing risks that are unowned, stalled, or under-mitigated for decision and escalation, and tracking residual risk after launch. - In partnership with colleagues who lead horizon scanning, use relevant external developments across AI safety and security research, public incidents, adversarial activity, industry standards, emerging technologies, and competitor products, as inputs to current risk prioritization and mitigation decisions at OpenAI. - Apply and refine practical frameworks and taxonomies for current agentic failure modes, control gaps, abuse patterns, and potential downstream harms across products, deployment environments, and user workflows, integrating them into the broader risk program. - Produce concise, decision-ready assessments that communicate key findings, assumptions, confidence levels, competing hypotheses, and prioritized recommendations for product, safety, security, policy, and leadership stakeholders, with accountable owners and next review points. - Define and track operating metrics for the agentic-risk program, including coverage, ownership, decision latency, mitigation status, and closure and partner with measurement experts on risk indicators and monitoring capabilities. - Partner with colleagues who lead evaluations, scenario analyses, tabletop exercises, red-team campaigns, and investigations focused on agentic systems, using their findings to drive actionable mitigations, accountable ownership, and measurable follow-through. YOU MIGHT THRIVE IN THIS ROLE IF YOU - Have significant experience—typically 7+ years—in trust and safety, integrity, security, cyber threat intelligence, AI safety, product risk, strategic intelligence, abuse investigations, or a related field. - Have a strong understanding of modern AI systems and agentic architectures, including hands-on experience using, evaluating, or building agentic systems. You are familiar with AI safety concepts, agentic failure modes, and misalignment risks, and can reason about how agent objectives, incentives, environments, and system design choices may produce unintended or harmful outcomes. - Have demonstrated experience analyzing how harmful outcomes emerge from interactions between users, products, and technical systems, and can assess how increasingly capable agentic systems may amplify, automate, or transform existing abuse vectors such as fraud, scams, social engineering, coordinated influence operations, cyber abuse, or other forms of platform misuse. You have also helped operate a cross-functional risk, safety, security, or integrity program, clarifying ownership, resolving dependencies, escalating gaps, and driving follow-through without direct authority. - Have exceptional analytical judgment and experience producing assessments under uncertainty. You can identify weak signals, develop and test hypotheses, distinguish signal from noise, communicate assumptions and confidence levels clearly, and update your conclusions as new evidence becomes available. - Possess strong technical fluency and are comfortable engaging deeply with engineers, researchers, and security practitioners. You do not need to be an engineer, but you should be able to translate technical findings into clear risk assessments. - Are comfortable synthesizing data and evidence from multiple sources to manage a current risk portfolio, including investigations, telemetry, evaluations, experiments, dashboards, and external research. Experience using SQL, Python, and analytical tools is a plus. - Have experience applying risk frameworks, threat models, severity assessments, taxonomies, or prioritization frameworks to structure current operational ambiguity and support decision-making. - Communicate complex topics clearly and effectively, producing concise, executive-ready analysis and influencing stakeholders across technical and non-technical teams. - Thrive in fast-moving environments, balancing rigor with pragmatism while building lightweight operating processes and tools that improve organizational coordination and follow-through on material risks. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.", "summaryDescription" : "Agentic Risk Analyst at OpenAI. Skills: Agentic risk, Risk analysis, Threat intelligence. Build and maintain risk portfolio. Map risks to workstreams", "createdAt" : "2026-06-14T04:13:57.698", "lastUpdated" : "2026-06-15T12:06:15.923", "ingestTimestamp" : "2026-06-14T04:13:57.698", "mongoId" : "6a2cb02174d8ee00a09d8fa4", "processingStatus" : "llm_updated", "llmProcessingStatus" : true, "salaryAnnualMin" : 288000, "salaryAnnualMax" : 425000, "salaryBand" : "200k+", "hasSalary" : true, "allSkills" : [ "Risk assessment", "Threat analysis", "Data synthesis", "Signal analysis", "Impact assessment", "Severity assessment", "Evidence assessment", "Uncertainty assessment", "Priority assessment", "Action recommendation", "Launch readiness", "Risk escalation", "Risk tracking", "Horizon scanning", "Failure mode analysis", "Control gap analysis", "Harm analysis", "Stakeholder communication", "Metric definition", "Metric tracking", "Risk indicators", "Monitoring capabilities", "Agentic risk", "Risk analysis", "Threat intelligence", "Strategic perspective", "System-level perspective", "Adversarial misuse", "Unintended behavior", "Risk prioritization", "Mitigation strategy", "Forecasting", "Scenario work", "Decision making", "Coordination", "Product decisions", "Safety mitigations", "Governance", "Agentic systems", "AI safety", "AI security", "Adversarial activity", "Emerging technologies", "Autonomy", "Multi-step task execution", "Tool use", "Memory", "Retrieval", "Connectors", "Computer-use capabilities", "Multi-agent workflows" ], "skillCount" : 51, "jobCategory" : "engineering", "jobSubcategory" : "software", "seniorityLevel" : "Mid", "dataQualityScore" : 0.7777778, "_score" : 604.28156, "hasLocation" : true, "hasGeo" : true, "llmIndustry" : "Technology", "llmIndustryConfidence" : 0.95 } ], "status" : 200, "message" : "OK", "pagination" : { "page" : 0, "limit" : 50, "totalCount" : 31042, "totalPages" : 621, "hasNext" : true, "hasPrevious" : false } }

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