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 Skills : Must have hands-on proficiency with at least two agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI), direct SDK experience with Anthropic Claude API, OpenAI Assistants API, or Vertex AI Agent Builder, Python mastery, RAG pipeline depth, cloud deployment experience (AWS/Azure/GCP), and agent observability experience (LangSmith, Helicone).

- Domain Expertise : Must have working knowledge of pharma commercial data and experience operating in regulated data environments (GxP, 21 CFR Part 11, HIPAA).

- Availability : Must be an immediate joiner or currently serving notice period.

- Note : Role is Hybrid, WFH flexibility as well upto 6 days a month. CTC is inclusive of 10% variable.