Senior Manager, AI Engineering

This is an opportunity to play a key role in building next-generation capabilities that support Pfizer's Global Clinical Supply Organization (GCS) and accelerate its digital transformation journey. The Senior Manager, AI Engineering is a global technical leadership role responsible for designing, delivering, and scaling AI-powered products, data platforms, analytics solutions, and digital capabilities that enhance decision-making, operational effectiveness, and digital transformation across GCS . Partnering with business, Digital, Product, Data Science, and technology teams worldwide, the role translates complex clinical supply challenges into secure, scalable, and business-impacting solutions. The position combines strategic technical leadership with practical engineering depth, requiring the ability to architect, prototype, guide development, and operationalize AI-enabled solutions while shaping solution architecture, engineering approaches, and delivery execution. Operating with a high degree of independence, this role helps advance the adoption of AI and data-driven capabilities by transforming innovative concepts into production-ready solutions that deliver measurable business value. This role reports directly to the Global Clinical Supply Central Operations Network Strategic Hub and AI/Data Analytics & Reporting Lead.

Responsibilities Lead the technical delivery of priority AI, data engineering, analytics, automation, and digital product capabilities for Global Clinical Supply (GCS) AI, Data Analytics & Reporting, ensuring solutions are scalable, secure, supportable, and aligned with business priorities. Translate complex business opportunities and operational pain points into pragmatic AI and data solution approaches, applying sound judgment to balance value, feasibility, risk, compliance, sustainability, and adoption. Provide technical leadership across cross-functional delivery teams, guiding solution design, engineering practices, delivery execution, and product-quality outcomes through expertise, influence, and matrix leadership. Establish and promote reusable engineering patterns, architecture approaches, and delivery standards for AI-enabled solutions, including data pipelines, cloud-native development, analytics platforms, AI lifecycle management, MLOps/LLMOps, Retrieval-Augmented Generation, and agent-based capabilities. Drive the transition of AI, analytics, and automation solutions from experimentation or prototype stages into production-ready, maintainable, monitored, and operationally sustainable capabilities. Partner with GCS, Digital, product, analytics, data science, and enabling-function stakeholders to align priorities, manage dependencies, shape delivery sequencing, and support adoption of AI and analytics capabilities. Evaluate technical trade-offs and dependencies across data availability, integration, platform constraints, quality, security, Responsible AI considerations, scalability, and user impact, making recommendations that support mid-term business and technology objectives. Communicate complex technical concepts, risks, options, and recommendations clearly to business, technical, and leadership audiences to support informed decision-making and effective execution.

Required Qualifications Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, Artificial Intelligence, or a related discipline; equivalent practical experience may be considered where appropriate. 7+ years of experience leading and delivering AI engineering, software engineering, data engineering, advanced analytics, automation, or digital product solutions within complex enterprise environments. Proven track record of leading or co-leading complex technology initiatives across cross-functional teams and delivering measurable business outcomes. Strong knowledge of AI solution architecture and implementation, including AI engineering, machine learning, predictive and