Director, AI Engineering Excellence Lead

Role Summary

Director, AI Engineering Excellence Lead. 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 that every AI solution meets enterprise-grade standards for quality, maintainability, and compliance. This role focuses on technical delivery orchestration, partnering with Portfolio Management and Program Operations to align on reporting, governance, and prioritization. The role establishes the AI Engineering Community of Practice, maintains cross-pillar synchronization, and promotes the visibility of Applied AI Engineering (A2E). Reporting to the Head of Applied AI Engineering, this role blends deep technical leadership, product engineering strategy, and enablement of enterprise use cases, with execution across 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, interfacing with business, platform, and cross-center teams.
• Drive alignment between the Applied AI Engineering vision and execution through standards, frameworks, and delivery practices.
• Translate business requirements into technical deliverables aligned 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.
• 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 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 in 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 quality/safety practices.
• Required: Experience managing cross-team dependencies and communicating status at multiple levels of the organization.
• Required: Exceptional organizational and communication skills.
• 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.

Skills

• Strategic leadership and cross-functional collaboration
• Technical translation of business requirements to AI solutions
• Documentation development and knowledge management
• Program governance, planning, and execution
• Strong communication and stakeholder management
• Compliance and safety considerations in AI engineering

Education

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

Additional Requirements

• Work Location: Must be able to work from assigned Pfizer office 2-3 days per week, or as needed by the business
• Travel: Not specified as a major requirement