Director, AI Engineering – Clinical Development and Operations

Role Overview

• Develop and Implement AI Solutions: Build and deploy AI/ML models and solutions that support process-heavy workflows (e.g. protocol feasibility and site selection, study start-up etc.) including documentation, and operational reporting.
• Contribute to the automation of manual and repetitive activities to improve speed, quality, and consistency.
• Strengthen Operational Decision-Making: Develop predictive, optimization, and scenario-based models to support clinical trial supply forecasting and operational planning.
• Create and maintain dashboards and decision-support tools that translate complex data into actionable insights for CD&O leadership and operational teams.
• Engineer Production-Grade AI Systems: Implement AI solutions that are aligned with data integrity standards and governance best practices, including model validation, versioning, and monitoring.
• Design and implement AI agentic solutions that can plan and execute multi-step workflows.
• Build robust, production-ready ML and analytics pipelines with a focus on reproducibility and scalability.
• Deploy AI solutions in cloud environments, ensuring reliability, security, and seamless integration with existing systems.
• Collaborate Across Disciplines: Partner closely with CD&O line teams, scientists, and Digital partners to ensure that AI efforts remain tightly aligned to real scientific needs and can be deployed in ways that are trusted, scalable, and adopted in day-to-day work.
• Champion best practices in AI engineering system lifecycle.

Requirements

• PhD in Computer Science, Machine Learning, Data Science, Software Engineering, AI, or a related discipline and a minimum of 5 years of applied analytical experience with demonstrated impact in operations, automation, business analytics, or decision support OR Master’s in Computer Science, Machine Learning, Data Science, Software Engineering, AI, or a related discipline and a minimum of 7 years of applied analytical experience with demonstrated impact in operations, automation, business analytics, or decision support.
• Strong hands-on experience applying LLMs, generative AI, machine learning, or related AI approaches to real-world workflows, products, or analytical use cases, ideally within R&D, clinical operations or large-scale regulated organizations.
• Experience building practical, reusable workflows or systems rather than one-off analyses, with strong implementation skills in Python and modern AI / ML tooling.
• Sound judgment regarding methodological rigor, model limitations, evaluation, and the appropriate role of human oversight in AI-enabled workflows.
• Experience working directly with domain users or stakeholders to translate ambiguous needs into useful technical solutions, with evidence of strong collaboration and communication skills.

Tech Stack

• Cloud
• Python

Benefits

• Health benefits to include medical, prescription drug, dental and vision coverage.
• 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution.
• Paid vacation, holiday and personal days.
• Paid caregiver/parental and medical leave.
• Comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments.