Architect
Technology
Architect
Neural analysis suggests this role is
optimal for Senior candidates.
“Architect at Architect. Skills: Agentic AI, LLM Technologies, Full Stack Development, DevOps, Cloud Services. Design and architect RAG pipelines. Design and architect Vector Databases”
What You'll Achieve.
Achieve business goals; Powering 50+ enterprise grade agent use cases
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
8 - 15 Years experience, Expert in building autonomous systems, Expert in multi-agent workflows, Expert in Python (FastAPI/Django), Expert in Node.js, Expert in Docker, Expert in Kubernetes, Expert in CI/CD pipelines, Expert in GitLab CI, Expert in GitHub Actions, Expert in Jenkins, Expert in LangSmith, Expert in Trulens, Expert in Prometheus, Expert in Grafana, Expert in ELK, Proven ability to lead technology teams, Proven ability to mentor engineers, Proven ability to drive technical strategy, Proven ability to drive innovation, Proven ability to drive end-to-end project delivery, Expert in managing cross-functional stakeholders, Expert in agile methodologies, Expert in high-quality code reviews, Expert in documentation, Expert in clear communication
Nice to Have
Familiarity with Infrastructure as Code (Terraform), Familiarity with monitoring tools (Prometheus, Grafana, ELK)
What You'll Do.
Design and architect RAG pipelines
Design and architect Vector Databases
Design and architect multi-agent orchestration systems
Integrate upstream/downstream systems
Lead end-to-end development of full-stack applications
Develop backend services
Develop UI components for agent configuration
Support robust DevOps practices
Drive robust DevOps practices
Ensure production-grade deployments
Implement auto-scaling
Implement fault tolerance
Implement disaster recovery
Own end-to-end delivery from PoC to production
Collaborate with cross-functional teams
Maintain high-quality documentation
How You'll Work.
Team & Collaboration
Cross-functional teams; Cross-functional stakeholders
Communication Scope
Clear communication
Process & Methodology
Agile delivery, Agile methodologies, End-to-end project delivery
Full Job Description
While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi! **Role: Technical Architect – Agentic AI & Software Development** **Experience Level: 8 - 15 Years ** **Work Location: Bangalore / Mumbai ** **What You 'll Do** You will be working as a Solution Lead designing and delivering Agentic AI platforms and applications that are running across multiple geographies, helping organizations achieve their business goals with the use of full stack technologies, cloud services, DevOps, and cutting-edge AI/ML capabilities. We are building scalable Agentic AI platforms, powering 50+ enterprise grade agent use cases. This role requires end-to-end ownership across the entire Agent Development Lifecycle (ADLC) - from requirements gathering to production deployment and beyond. **Role & Responsibilities** * Design and architect advanced RAG pipelines, Vector Databases, and multi-agent orchestration systems with upstream/downstream integrations * Lead end-to-end development of scalable full-stack applications including backend services, APIs, and intuitive UI components for agent configuration * Support and Drive robust DevOps practices ensuring production-grade deployments with comprehensive monitoring, auto-scaling, and fault tolerance * Own end-to-end delivery from PoC to production, mentor engineers, and collaborate with cross-functional teams while maintaining high-quality documentation **Skill Requirements - Must Have** **Agentic AI & LLM Technologies (Primary Skills)** * Agentic Frameworks & Orchestration: Expert in building autonomous systems and multi-agent workflows using frameworks like LangChain, CrewAI, or AutoGen, inclu
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