Staff, AI Product Manager
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.
Tell new capability from repackaging
Strategic Prioritization & Portfolio Shaping
Shape the emerging tech portfolio.
Make the graduate, retire, or hold call.
Protect the estate from sprawl.
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 Intelligence, Change Management, Data Analysis, Feature Prioritization, Machine Learning (ML), Machine Learning Model Management, ML Platforms, Model Evaluation, Performance Analysis, Product Delivery, Product Design, Product Lifecycle Management (PLM), Product Roadmapping, Product Strategies, Roadmap Development, Statistical Analysis, User Needs Analysis
Uniting science, technology and talent to get ahead of disease together.
Inclusion at GSK
Important notice to Employment businesses/ Agencies
Not included in the source posting: about the role, benefits.
Skills
Who can apply
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