Company
Engineering
AIEngineer(Mid-Level)
Neural analysis suggests this role is
optimal for Mid candidates.
“AI Engineer (Mid-Level). Skills: Agentic systems, LLM services, RAG pipelines. Design agentic systems. Build agentic systems”
What You'll Achieve.
Deliver measurable user impact
Industry & Context.
Sound judgment
What You'll Do.
Design agentic systems
Build agentic systems
Maintain agentic systems
Own retrieval infrastructure
Implement orchestration
Implement tool-calling
Implement memory components
Implement reasoning components
Develop evaluation infrastructure
Develop safety infrastructure
Measure model performance
Implement frontend code
Implement backend code
Operate production systems
Collaborate with leadership
Collaborate with product
Collaborate with design
Define success metrics
Iterate based on feedback
Iterate based on telemetry
How You'll Work.
Team & Collaboration
Leadership; Product; Design
Full Job Description
ABOUT THE ROLE This is a mid-level AI Engineer role on the core product team, focused on building agentic systems that automate complex, multi-step workflows across regulated and enterprise domains. You'll work across the full stack to ship production LLM-based services, ensure reliability and safety, and collaborate with leadership, product, and design to deliver measurable user impact. WHAT YOU'LL DO - Design, build, and maintain agentic systems that automate complex, multi-step workflows across healthcare, legal, fintech, logistics, and compliance domains. - Own production retrieval-augmented generation (RAG) pipelines and retrieval infrastructure including vector databases, embeddings, and indexing for domain-specific search at scale. - Implement multi-agent orchestration, tool-calling, memory, and reasoning components to deliver robust AI-driven user experiences. - Develop evaluation and safety infrastructure to measure model performance, surface regressions, and enforce enterprise-level trust and reliability. - Ship full-stack AI products from MVP to enterprise-grade by designing APIs and data models, implementing frontend and backend code, and operating production systems with CI/CD, monitoring, and testing. - Collaborate with leadership, product, and design to prioritize work, define success metrics, and iterate based on user feedback and telemetry. WHAT WE'RE LOOKING FOR - 2–8 years of software engineering experience with demonstrated delivery of shipped user-facing or backend products. - Practical experience deploying LLMs or LLM-based services in production, including prompt design, orchestration, and tool integration. - Proficiency across the stack: Python plus TypeScript/React (or equivalent), and experience with cloud platforms (AWS or GCP) and relational or NoSQL databases. - Working knowledge of RAG patterns, vector databases, embeddings, and retrieval pipelines, with sound judgment to choose appropriate approaches. - Experience building automated te
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