- 5–7 years in software or ML engineering; 2+ years building and shipping production LLM or
- agentic AI systems.

- Hands-on proficiency with at least two agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI); you have debugged framework internals, not just followed tutorials.

- Direct SDK experience: Anthropic Claude API (tool use, streaming), OpenAI Assistants API, or Vertex AI Agent Builder.

- Python mastery: production-quality code, type annotations, unit and integration tests, packaging, and performance profiling.

- RAG pipeline depth: embedding model selection, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, RAGAS or custom evaluation harnesses.

- Cloud deployment: AWS, Azure, or GCP. Docker, Kubernetes, IaC basics (Terraform or CDK), CI/CD pipelines.

- Agent observability: LangSmith, Helicone, or equivalent — you have diagnosed latency, cost, and quality issues in production traces.

- Working knowledge of pharma commercial data: Rx/claims, NPI-level analytics, brand performance metrics.

- Experience operating in regulated data environments: GxP, 21 CFR Part 11, HIPAA- compliant data handling.

📌 Lead AI Engineer – Agentic Systems (Pharma / Life Sciences Domain is mandatory) (Bengaluru)
🏢 Talentquell
📍 Bengaluru