Roles & Responsibilities

- Design and implement complex components of agentic pipelines — multi-agent graphs, tool orchestration layers, retrieval modules, and memory systems — using LangGraph, AutoGen, CrewAI, or equivalent
- Take ownership of full sub-system designs: define agent topology, data flows, API contracts, and failure handling for a bounded scope
- Build and optimise production RAG pipelines: document ingestion, chunking strategy, embedding selection, hybrid search, retrieval evaluation, and latency tuning
- Integrate agentic systems with pharma data platforms (IQVIA, Symphony, Komodo, Veeva) via REST, event-driven hooks, and batch pipeline patterns
- Own observability for components: instrument trace logging, cost metrics, drift alerts, and evaluation harnesses using LangSmith, Helicone, or equivalent
- Lead CI/CD for owned modules: containerisation (Docker/Kubernetes), automated test suites, staging gate criteria, and rollback procedures
- Translate medical affairs, commercial analytics, and clinical ops requirements into agent component specifications
- Apply 21 CFR Part 11 auditability, HIPAA-compatible data handling,



and GxP traceability patterns to every component
- Build intelligent document processing pipelines for pharma content: drug labels, clinical study reports, HEOR dossiers, and regulatory submissions
- Contribute to KOL mapping, competitive intelligence, and signal detection agents with domain-aware retrieval and reasoning strategies
- Serve as the day-to-day technical reference for AI Engineers on the pod: code review, design feedback, unblocking implementation issues
- Lead component-level design reviews and surface architecture risks before they reach staging
- Pair with junior engineers on hard problems and document patterns and decisions in the team's shared knowledge base
- Represent engineering quality in client-facing technical discussions and translate complex trade-offs into plain language
- Contribute reference implementations and guardrail templates to the firm's internal agentic AI playbook

Interested candidate send resume to [email protected] Pay: ₹2,200,000.00 - ₹3,600,000.00 per year

Work Location: In person

📌 Lead AI engineer(agentic system,pharma domain) (Bengaluru)
🏢 TalentXO
📍 Bengaluru