Drive the AI-native Development Operations strategy and roadmap, anchored to measurable clinical trial outcomes.
Lead prioritization 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 and roadmap 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, use AI-native development tools to run hands-on experiments with 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 identify 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.
Requirements
Bachelor’s degree in Life Sciences, Engineering, Computer Science, or a related field
Extensive experience in Pharma strategy, applied AI/technology, or related roles
Deep understanding of clinical operations and wider clinical development, gained in industry, consulting or other relevant settings
Strong knowledge of industry trends and technologies shaping the future of clinical trials
Demonstrated experience building business cases and delivering AI-enabled transformation programmes with measurable business outcomes
Practical fluency across AI, data and technology topics to work effectively with technical teams
Strong commercial judgement and experience shaping vendor decisions in complex enterprise settings
Exceptional written and verbal communication, with the ability to translate complex strategic and technical topics for senior, non-technical audiences
Hands-on experience with AI-native development tools, including frontier agentic development tools (e.g. Claude Code, Codex), and rapid prototyping practice.
Benefits
health care and other insurance benefits (for employee and family)