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 quality, maintainability, and compliance of AI solutions. It focuses on technical delivery orchestration in partnership with central program teams to align reporting, governance, and prioritization, and establishes the AI Engineering Community of Practice to promote cross-pillar synchronization and visibility of Applied AI Engineering.

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 as the primary interface 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 and platform capabilities.
• Guide feasibility, scope, and best practices for AI engineering, including performance, scalability, and compliance considerations.
• Align and integrate engineering work across the 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.
• Maintain a centralized engineering playbook and reusable frameworks for rapid, compliant delivery.
• Establish an AI Engineering Community of Practice to set best practices and standards across the enterprise.
• 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.

Qualifications

• Required: 8‚Äì10+ years in software/AI engineering roles, with 3+ years in technical leadership or engineering excellence functions.
• Required: Bachelor‚Äôs 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 with the 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 with the ability 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.

Additional Requirements

• Location: Must be able to work from a Pfizer office 2‚Äì3 days per week, or as needed by the business.