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 leads a team of AI engineers and technical writers to ensure enterprise-grade standards for quality, maintainability, and compliance, and works in close partnership with central Portfolio Management and Program Operations teams to align on reporting, governance, and prioritization.

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