AI Director, Development Global Clinical Operations

This role sits within DP&I (Development Operations Platforms & Innovation), part of Development Global Clinical Operations at GSK. DP&I is building the capability to deploy AI at scale across clinical operations and the wider Development Operations function, with a mandate to help reshape how GSK plans, delivers, and continuously improves clinical trials.

DP&I develops and deploys scalable, AI-native capabilities, shared foundations, and new ways of working across Development Operations. Working across clinical operations, technology, product, data, and external partners, the team builds the platforms, products, and partnerships needed to turn innovation into measurable value.

Job Purpose

As AI Director, you will drive the AI-native Development Operations strategy: defining where AI can create meaningful value across Development Operations, building and testing concepts hands-on using frontier tools, and shaping how priority capabilities move from concept to scaled deployment. You will work directly with business SMEs and enterprise technology teams to prototype, pressure-test, and deploy AI-enabled workflows. Where external capability is needed, you will lead vendor evaluation and shape build-buy-partner decisions with commercial rigour. This role combines strategy, hands-on solution building, and deployment judgement. It requires structured problem-solving, strong commercial and enterprise credibility, and hands-on fluency with frontier agentic development tools. This role reports into the Head of Asset Acceleration and AI.

You will shape how GSK uses AI to measurably accelerate trial delivery and improve outcomes for patients.

Key Responsibilities

• Drive the AI-native Development Operations strategy and roadmap, anchored to measurable clinical trial outcomes.
• Lead prioritisation for AI opportunities across Development Operations in line with the AI-native Development Operations strategy and R&D priorities.
• Continuously scan the external landscape for emerging AI capabilities, frontier tools, vendor offerings, and new ways of working, translating relevant developments into clear implications for Development Operations strategy, portfolio priorities, and build-buy-partner choices.
• Define the build-buy-partner approach for each priority capability, including vendor and partner evaluation where needed, balancing speed, differentiation, risk, cost, and long-term platform value.
• Build and defend business cases with clear ROI, payback logic, and success criteria; enforce stage-gate discipline, including the decision to stop or reshape initiatives that do not demonstrate value.
• Shape the deployment strategy, roadmap and solution architecture with enterprise AI, technology, data, security, regulatory, and quality teams to ensure scalable and compliant delivery using shared foundations rather than one-off point solutions.
• Drive cross-functional alignment and endorsement for the AI-native Development Operations strategy across the enterprise.
• Partner with leaders across R&D to identify priority workflow bottlenecks, define measurable outcomes, and shape AI-native capabilities.
• Lead 0-to-1 incubation for priority opportunities: frame hypotheses, build and test working prototypes hands-on alongside technology teams and business SMEs, and define the evidence required to scale, reshape, or stop.
• Define adoption strategy for priority AI-native capabilities, including workflow redesign, user readiness, and change interventions required for scaled deployment.

Stakeholder Management:

• Leaders across R&D to shape strategy, priorities, secure sponsorship and align on value.
• Leaders across enterprise AI, technology, security, and quality teams to enable scalable deployment.
• Strategic relationships with external vendors, consulting partners and technology providers to assess capabilities, shape partnerships and deliver value.
• Frontline users across Development Operations to ensure solutions solve real problems and value is realised at scale.

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Why You?

Basic Qualifications:

• Bachelor’s degree in Life Sciences, Engineering, Computer Science, or a related field.
• Extensive experience in applied AI/technology or Pharma strategy, gained at a leading AI or technology consultancy, the AI practice of a top-tier strategy consultancy, or a comparable applied-AI environment.
• Deep understanding of clinical operations and wider clinical developme…