Asso Director / Director - Agentic AI

TECHNICAL DEPTH (REQUIRED)

· 8+ years in software or ML engineering; 3+ years with production LLM or agentic AI systems.

· Hands-on proficiency with agentic frameworks: LangGraph, LangChain, AutoGen, CrewAI, or equivalent. Model Context Protocol (MCP) familiarity strongly preferred.

· Direct SDK experience: Anthropic (Agents SDK, tool use, Claude API), OpenAI (Assistants API, function calling), Google (Vertex AI Agent Builder, Gemini API). Model Context Protocol (MCP) strongly preferred.

· Python fluency. Ability to build, test, and deploy production code, not just notebooks.

· Strong RAG architecture skills: chunking strategies, embedding models, vector stores, knowledge graphs for entity-relationship modeling (drug-indication-HCP-trial), hybrid search, retrieval evaluation.

· Cloud-native deployment: AWS, Azure, or GCP. Containerization (Docker, Kubernetes), CI/CD, infrastructure-as-code.

· Observability tooling for AI systems: logging agent traces, eval frameworks, cost management, drift detection.

PHARMA / LIFE SCIENCES DOMAIN (REQUIRED)

· Working knowledge of pharma commercial data ecosystems: Rx/claims data, NPI-level analytics, market access, brand performance

· Familiarity with regulated data environments: GxP, 21 CFR Part 11, HIPAA-compliant data handling, audit trail requirements

· Exposure to at least two of: medical affairs analytics, real-world evidence, clinical operations data, or HEOR/market access workflows

· Comfort reading and reasoning over scientific and regulatory documents: labels, clinical study reports, AMCP dossiers, payer briefs

LEADERSHIP & COMMUNICATION (REQUIRED)

· 5+ years leading technical teams or delivery workstreams, including mentoring engineers and managing project scope and timelines

· Track record of shipping production AI solutions with measurable business impact, not just proof-of-concepts

· Comfortable in executive-level conversations: scoping engagements, presenting architecture trade-offs, and aligning on governance expectations

· Strong written communication. You can write a crisp technical spec and a clear client-facing proposal without switching tools

GOOD TO HAVE

· Experience with Veeva Vault, Medidata, or IQVIA platform integrations

· Knowledge of reinforcement learning from human feedback (RLHF) and fine-tuning workflows

· Familiarity with EU AI Act and emerging FDA guidance on AI/ML in clinical and regulatory contexts

· Prior consulting or services-firm experience: multi-client delivery, proposal development, engagement management