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 settings: GxP, 21 CFR Part 11, HIPAA- compliant data handling.

📌 Lead Ai Engineer – Agentic Systems Pharma / Life Sciences Domain Is Mandatory Bengaluru (India)
🏢 Talentquell
📍 India