Staff, AI Product Manager-Emerging Tech and AI Tooling

Job Purpose : This is not a traditional enterprise product role managing a source system’s roadmap, releases, and backlog. As an AI Product Manager in Enterprise AI, you: • Build new AI products from ambiguous, unsolved business problems. • Work with probabilistic systems, defining evaluations, acceptable error, and human oversight. • Help lead a bionic pod, deciding which work goes to engineers and which to AI agents and workers, and how they hand off. • Prototype hands on and are measured on business outcomes. • Owns the evaluation portfolio for new AI tools and platforms across Enterprise AI. • Decides what graduates into a standing platform tower, what holds, and what gets retired. • Owns the AI developer tooling estate end to end. • Hands graduated platforms over with a working operating model. Responsibilities: Evaluation & Graduation • Run every evaluation to a decision. Set the hypothesis, the success bar, the comparison set, and the kill date up front. Keep a live view of what is in flight, on hold, or retired. • Quantify value rigorously. Build credible adoption and retirement cases that survive finance and architecture scrutiny — engineering hours saved, licence cost avoided, capability gained, duplication removed. • Tell new capability from repackaging so overlap with what GSK already runs is caught before it becomes duplicate spend. Strategic Prioritization & Portfolio Shaping • Shape the emerging tech portfolio. Keep a living view of in-flight, queued, and retired evaluations with the rationale for each call, and feed it into the AI Platforms & Tools portfolio. • Make the graduate, retire, or hold call. Decide which tower receives a graduating platform, and hold the decision date when the organisation would rather extend it. • Protect the estate from sprawl. Say no, with evidence, to tools that look attractive but do not change what the organisation can actually do. Required skil ls: • 16+ years of progressive experience spanning some combination of pharma/life sciences, AI/ML product strategy, and senior product management or strategy roles in technology-led organisations. • Demonstrated track record of identifying, scoping, prototyping, and shepherding high-value technology or AI initiatives from problem framing through funding into delivery. • Strong working knowledge of enterprise AI platforms and developer tooling — how they are licensed, entitled, supported, and adopted at scale — and of at least one part of the pharma value chain. • Solid technical fluency in modern AI/ML — LLMs, agentic systems, AI agents and workers, ML lifecycle, data and evaluation patterns — sufficient to leverage evidence from rapid prototyping to challenge engineers, scope realistically, and avoid hype-driven choices. • Experience leading a small engineering team while operating with a span of influence far wider than the headcount — leading through frameworks, evidence, and quality of thinking. • A product management or product-strategy heritage: discovery, opportunity sizing, roadmap shaping, prototyping, and stakeholder alignment — ideally on products whose core behaviour is AI rather than conventional software. Preferred skills: • Hands on with the AI platform ecosystem as a daily practitioner: fluent in how the landscape is categorised, where the category boundaries actually fall, and which capabilities are genuinely distinct from each other. • Able to evaluate from first principles and to design the evaluation itself: set the hypothesis, the success bar, the comparison set, and the decision date, and defend the method to engineers and vendors alike. • A proven record of retiring and consolidating technology, including at least one tool killed on evidence. #AGTech Skills AI Platforms, Artificial Intel