Role Summary
The AI Engineering Excellence Lead drives coherence, quality, and scalability across the Applied AI Engineering function. This role leads 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 PfizerβΓΓ΄s central Portfolio Management and Program Operations teams to align 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 to the Head of Applied AI Engineering, you will manage a team of senior AI Engineers and Technical Writers, blending deep technical leadership with product engineering strategy and enablement of enterprise use cases.
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 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.
- 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 to set 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: 8βΓΓ¬10+ 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 the 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, with 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.
Skills
- Technical leadership and team management
- Enterprise architecture alignment
- Documentation and technical writing
- Strategic planning and governance
- Stakeholder engagement and cross-functional collaboration
- AI/ML solution delivery lifecycle and quality practices
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