AI Acceleration Lead

Responsibilities support the AI-native Development Operations strategy through the design and delivery of AI pilots that address real operational problems in clinical development work hands‑on with clinical operations users, vendors, and enterprise partners to shape hypotheses, test solutions in practice, build evidence of value, and make clear recommendations on what should stop, iterate, or scale help scale solutions from pilot to enterprise adoption and drive measurable impact to clinical development proactively identify AI opportunities across Development Operations by scanning workflows, engaging clinical operations teams, and spotting where AI can create meaningful value; translate real bottlenecks into clear pilot hypotheses and practical success criteria maintain an active outside‑in view of emerging AI capabilities, workflow innovations, and evolving ways of working, and convert those signals into strategic recommendations, roadmap updates, and new opportunity areas scope and run AI pilots end‑to‑end, including design, delivery approach, execution oversight, and recommendations on whether to stop, iterate, or scale partner with vendors and enterprise technology teams to ensure pilots are robust, compliant, usable, and positioned to scale using shared foundations if successful manage delivery risks, dependencies, and partner performance across active pilots to maintain momentum and execution quality build proof‑of‑value cases using measures including time saved, quality improvement, user adoption, risk reduction, and readiness to scale use AI‑native development tools to run hands‑on use‑case testing alongside technology teams and business SMEs, validating feasibility and value before committing to full deployment inform portfolio and investment decisions by identifying patterns across pilots, synthesising pilot findings, adoption data, and operational intelligence, and making evidence‑based recommendations on what to prioritise, accelerate, reshape, or stop drive adoption for priority AI‑native capabilities, including workflow redesign, user readiness, and change interventions required for scaled deployment Qualifications Bachelor’s degree in Life Sciences, Engineering, Computer Science, Business, or a related field 4+ years of experience in Pharma strategy, applied AI/technology, transformation, or programme delivery roles Experience in clinical operations and wider clinical development, gained in industry, consulting or other relevant settings Experience solving ambiguous problems and turning analysis into action Experience moving from problem definition through pilot design to clear recommendation, with ownership of delivery end‑to‑end Experience working across users, partners, and cross‑functional teams to deliver measurable outcomes in fast‑moving, ambiguous environments Experience with AI‑native development tools, including frontier agentic development tools (e.g. Claude Code, Codex), and rapid prototyping practice #J-18808-Ljbffr Jobtailor