Lead AI Engineer (Agentic Systems, Pharma domain)

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