Lead AI Engineer - Agentic Systems

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.

Ideal Candidate : Profile :

• Strong Lead AI Engineer Profile with agentic systems architecture expertise and pharma regulated-environment experience.

Experience :

• Must have 6+ years of software or ML engineering, with at least recent 2+ years building and shipping production LLM or agentic AI systems in pharma domain.

Tech Stack :

• Frameworks : LangGraph, LangChain, AutoGen, CrewAI.