​​VP, Chief AI Architect​

ROLE SUMMARY 

Pfizer is seeking a Vice President, Chief AI Architect to define and steward the enterprise AI architecture vision, roadmap, and governance that enable breakthroughs at scale across R&D, Manufacturing, and Commercial. This role brings integrated, end‑to‑end thinking across data, models, platforms, and products; curates innovation from a strong external network; and ensures secure, reliable, cost‑effective patterns for AI solutions (including LLMs and agentic systems) in a regulated environment. 

The Chief AI Architect partners closely with the Head of AI CoE (who builds and operates our AI platforms) to ensure that reference architectures, standards, and guardrails are translated into scalable, reusable capabilities. Together, they accelerate adoption, improve reliability and time‑to‑value, and uphold Responsible AI principles. 

ROLE RESPONSIBILITIES  

Enterprise AI Architecture Vision & Strategy 

• Define the target‑state AI architecture (data, model, application, and infrastructure layers) that integrates advanced analytics, ML/LLM, knowledge/semantic technologies, and operational systems. 

• Establish the North Star for foundational capabilities: RAG and retrieval pipelines, agents/orchestration, vector search, feature stores, model registries, observability, evaluation, safety layers, etc. 

• Set architecture principles that balance innovation speed with compliance, reliability, and total cost of ownership. 

Reference Architectures, Patterns & Standards 

• Publish reference architectures and blueprints for priority use cases (e.g., scientific discovery assistants, GxP‑impacted automation, manufacturing QA, field engagement copilots). 

• Define LLMOps/MLOps standards (model lifecycle, evaluation, red‑teaming, monitoring, rollback, drift, lineage, documentation). 

• Codify security, privacy, and Responsible AI guardrails: data minimization, isolation patterns, PII/PHI handling, human‑in‑the‑loop, explainability, auditability, model risk controls. 

Roadmap & Architecture Governance 

• Own the enterprise AI architecture roadmap; align with business strategy and portfolio funding. 

• Chair an AI Architecture Review Board (AARB) and design authorities that provide fast, pragmatic guidance and approvals. 

• Manage technology lifecycle (emerging → adopt → scale → retire) for AI frameworks, model classes, toolchains, and platforms. 

Innovation Scouting & External Ecosystem 

• Maintain a strong external network (hyperscalers, model labs, hardware vendors, startups, academia, standards bodies) to scout, evaluate, and curate innovations. 

• Run evidence‑based proofs‑of‑value and bake successful patterns into the reference stack; shape build/partner/buy decisions with the Head of AI CoE <