ROLE SUMMARY

The VP, Head of AICoEwill focus on enabling consistent, high‑quality AI capabilities,including large language model(LLM) access,that can be confidently adopted acrossall Pfizerdivisions. The role is designed to bring greater clarity, prioritization, and operating rigor to the AICoE, ensuring that talent, platforms, and investments are aligned to Pfizer's most important business outcomes.

This position requires a leader who can combine technical depth, strategic thinking, and enterprise influence to help the AICoEmature from a growing capability into a core, mission‑critical function for the company.

ROLE RESPONSIBILITIES

Enterprise AI & LLM Platforms

• Build andoperatesecure, reliable, low‑latency AI/LLM platforms with clear SLAs/SLOs, cost and performance guardrails, and strong observability.

• Standardize access to approved foundation models and internal models, enabling consistent enterprise use while meeting compliance and privacy requirements.

• Drive architectural simplification, platform reuse, and a catalog of reusable AI services that accelerate delivery across functions.

Strategy, Prioritization & Operating Model

• Define a multi‑year AICoEstrategy and roadmap aligned to enterprise priorities; make decisive trade‑offs that focus talent and investment on the highest‑value outcomes.

• Shift from project-by-project execution to platforms, products, and capabilities with measurable value realization and transparent portfolio governance.

• Establish outcome‑based funding, clear ownership, and cadence for performance reviews to ensure delivery at scale.

Responsible & Inclusive AI at Scale

• Partneringclosely with Legal, Compliance, Privacy, and Security,embedResponsible AI by design: model risk management, validation, auditability, explainability, human‑in‑the‑loop controls, and regulatory readiness.

• Ensureequitableaccess to AI platforms, tools, and enablement so teams across geographies and functionsbenefitfrom shared capabilities and standards.

Enterprise Influence & Partnerships

• Serve as a trusted advisor to seniorleaders inacross the enterprise toalign initiatives, remove roadblocks, and accelerate adoption.

• Communicatea clear visionfor how AI accelerates Pfizer's scientific and operationalbreakthroughs;champion responsible speed in a regulated environment.

Talent, Culture & Ways of Working

• Raise the engineering and leadership bar: recruit, develop, andretaintop AI platform engineers, ML engineers, applied scientists, and AI product leaders.

• Set standards for software quality,MLOps/LLMOps, model lifecycle management, security, and SRE practices; promote craftsmanship and continuous learning.

• Foster a culture of pride, recognition, collaboration, and learning that enables teams to do their best work together.

QUALIFICATIONS

Basic Qualifications

• BS/BA degree required, higher degree preferred or relevant experience, 15+ years in technology/AI/advanced analytics leadership, including buildingand runningenterprise‑scale AI/ML or data platforms with high reliability and performance.

• Deep understanding of LLMs/foundation models, ML systems architecture,MLOps/LLMOps, security, and modern cloud platforms.

• Proven ability to shape strategy, prioritize portfolios, and influence senior executives in complex, matrixed organizations.

• Experienceoperatingin highly regulated environments (e.g., life sciences, healthcare, financial services) with strong compliance and audit disciplines.

• Demonstratedtrack recordof building high‑performing engineering organizations and cultivating inclusive, collaborative cultures.

• Significant experiencewithMLOpsframeworks (e.g., Kubeflow, SageMaker,MLflow) and a deep understanding of the inference stack (GPU orchestration, quantization techniques, and token-optimization).

• Expert-level knowledge of data privacy, security, and ethics in a regulated environment (HIPAA, GDPR,GxP).

Preferred

• Prior leadership of an AI Center of Excellence or platform product organization supporting multiple business units.

• Experience translating advanced science and technology into enterprise‑ready platforms adopted at scale across R&D, Manufacturing, and Commercial.

• Familiarity with Responsible AI frameworks, model risk governance, and validation approaches suitable for regulated use cases.

NON-STANDARDWORK SCHEDULE,TRAVELOR ENVIRONMENTREQUIREMENTS

OTHER INFORMATION

• May be eligible for Relocation services

• Postingexpirationdate March 16, 2026

Supervision

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