Director, GMP AI Engineering

Discover your role

• Own and execute the IOPS AI roadmap in alignment with business goals, including use-case intake, prioritization, and value measurement across a mature and growing project portfolio
• Operate and evolve AI governance within a GMP environment — maintaining the IOPS AI policy and governance framework, computer system classification, validation procedures, qualified access, and data integrity — in close partnership with Quality and functional stakeholders
• Sustain audit and inspection readiness for AI systems and governance processes; represent IOPS AI practices to internal and external assessors
• Deliver IOPS-specific AI use cases end to end with an established multidisciplinary team, from business-need translation through deployment, adoption, and measured value
• Lead AI education and enablement across IOPS — including fluency curricula for audiences from operators to executives, an embedded advocate network, and engagement channels that convert demand into adoption
• Partner with Regeneron’s enterprise AI organization to adopt corporate platforms, tools, and standards, adapting them for GMP use rather than building parallel capability
• Translate between technology and leadership, communicating AI strategy, risk, and value clearly to senior leaders across the organization
• Lead, develop, and mentor an established high-performing team, fostering a culture of innovation and continuous learning

This role requires

• BS/BA in Engineering, Science, or a related technical discipline
• Associate Director: 10+ years of industry experience required
• Director: 12+ years of industry experience required
• Equivalent combination of education and experience considered; level determined based on qualifications
• Proven experience leading applied AI programs across governance, delivery, and education or adoption in a regulated environment
• Direct experience operating AI or computerized systems in a GMP/GxP environment, including computer system validation, system classification, data integrity, and inspection readiness; pharmaceutical manufacturing or similarly regulated environment strongly preferred
• Track record of delivering AI and intelligent automation use cases with measurable business value in manufacturing or operations settings
• Experience building education, fluency, or enablement programs and champion or advocate networks that scale adoption without proportional headcount growth
• Working fluency with the modern AI landscape including language models, machine learning, and intelligent automation, with sufficient technical depth to lead engineers, evaluate solutions, and govern systems credibly
• Familiarity with Responsible AI principles; experience with model risk, model credibility, or AI validation and assurance frameworks a plus
• Demonstrated ability to lead through influence across organizational lines and advocate effectively for AI initiatives with executive audiences