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aws python rag langgraph llm📋 Description
- Architect and scale AI quality infrastructure across Lattice.
- Design end-to-end AI evaluation across offline, production tracing, and feedback.
- Define metrics and datasets; automate scoring to prevent regressions.
- Build reusable agent infrastructure (multi-turn workflows, LLM DAGs).
- Scale RAG pipelines and vector retrieval with reliability.
- Lead technical direction for agent quality and evaluation strategy.
🎯 Requirements
- 8+ years professional software; 5+ years AI/ML in production.
- Deep production experience with LLM systems (prompting, RAG, orchestration, eval).
- Experience building agentic systems (multi-step workflows) and failure modes.
- Strong AI evaluation methodology and statistical experimentation.
- Strong system design across scalability, latency, reliability, cost.
- Production-grade Python; LangGraph/LangSmith; Pinecone/vector store.
🎁 Benefits
- Medical, dental, life, AD&D, and disability insurance
- Wellness apps
- Paid parental leave and PTO
- Remote working stipend
- WFH office setup stipend
- Retirement plan and financial planning budget
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