Director, AI Engineering Excellence Lead

Role Summary

The AI Engineering Excellence Lead drives coherence, quality, and scalability across the Applied AI Engineering function. This role drives technical rigor, documentation standards, and cross-functional alignment across AI Engineering. You will lead a team of AI engineers and technical writers to ensure that every AI solution meets enterprise-grade standards for quality, maintainability, and compliance. This role focuses on technical delivery orchestration in partnership with Pfizer’s central Portfolio Management and Program Operations teams to ensure alignment on reporting, governance, and prioritization. The AI Engineering Excellence Lead will establish the AI Engineering Community of Practice, maintain cross-pillar synchronization, and promote the visibility of Applied AI Engineering (A2E). Reporting into the Head of Applied AI Engineering, you will manage a team of senior AI Engineers and Technical Writers, blending deep technical leadership, product engineering strategy, and direct enablement of enterprise use cases. You will partner with business and technical stakeholders to design and deliver robust, scalable solutions that demonstrate the value of AI across the enterprise. This role is execution-oriented with strong influence on the AI solution lifecycle—from ideation to hand-off.

Responsibilities

• Lead a cross-functional team of AI Engineers and Technical Writers focused on engineering excellence, documentation, and operational rigor.
• Represent AI Engineering across the enterprise, serving as the primary interface with business, platform, and cross-center teams.
• Drive alignment between the Applied AI Engineering vision and execution through clear standards, frameworks, and delivery practices.
• Translate business requirements into technical deliverables that align with AI solution design, enterprise architecture and platform capabilities.
• Guide internal teams and clients on feasibility, scope, and best practices for AI engineering, including performance, scalability, and compliance considerations.
• Align and integrate engineering work across the Applied AI Engineering organization, ensuring smooth handoffs and consistent standards between the teams.
• Define and enforce A2E protocols for design reviews, code quality, and deployment readiness.
• Own A2E OKRs, capacity planning, and cross-functional coordination with Solution Design, AI & Data Platforms, and Creation Centers (CCs).
• Maintain a centralized engineering playbook and reusable frameworks for rapid, compliant delivery.
• Establish an AI Engineering Community of Practice that will act as the central hub setting best practices and standards across the enterprise for AI Engineering.
• Lead the creation of technical documentation, solution diagrams, and operational runbooks for AI solutions.
• Maintain and evolve technical documentation, training, and onboarding materials for AI Engineering practices.
• Develop and deliver training programs on A2E standards, handoff protocols, and reusable frameworks for engineers and stakeholders.

Qualifications

• Required: 8‚Äì10+ years software/AI engineering roles, with 3+ years in technical leadership or engineering excellence functions.
• Required: Bachelor's degree in Computer Science, Engineering or related discipline.
• Required: Deep understanding of modern AI engineering practices (MLOps, LLMOps, API integration, RAG architectures, observability, safety), and enterprise-grade delivery.
• Required: Proven ability to translate business needs into technical designs and guide feasibility assessments.
• Required: Excellent stakeholder management and communication skills; ability to influence across engineering, product, and compliance teams.
• Required: Strong understanding of AI/ML solution delivery lifecycle and associated quality/safety practices.
• Required: Experience managing cross-team dependencies and communicating status at multiple levels of the organization.
• Required: Exceptional organizational and communication skills ‚Äî able to synthesize and report progress clearly.
• Preferred: Experience leading engineering excellence programs or center of excellence initiatives.
• Preferred: Background in agile delivery or lean execution frameworks tailored for AI experimentation and productization.

Education

• Bachelor's degree in Computer Science, Engineering or related discipline

Additional Requirements

• Work Location Assignment: Must be able to work from assigned Pfizer office 2-3 days per week, or as needed by the business