Staff, AI Product Manager

Overview

Staff AI Product Manager in Enterprise AI at GSK, building new AI products from ambiguous business problems, running evaluations to graduation, retirement or hold decisions, and owning the AI developer tooling estate end to end.

What you'll do

• Build new AI products from ambiguous, unsolved business problems, working with probabilistic systems and 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 be measured on business outcomes.
• Own the evaluation portfolio for new AI tools and platforms across Enterprise AI, setting the hypothesis, success bar, comparison set and kill date up front and running every evaluation to a decision.
• Quantify value rigorously, building adoption and retirement cases covering engineering hours saved, licence cost avoided, capability gained and duplication removed.
• Identify overlap with what GSK already runs so duplicate spend is caught early.
• Shape the emerging tech portfolio and feed it into the AI Platforms & Tools portfolio.
• Make the graduate, retire or hold call and decide which tower receives a graduating platform.
• Protect the estate from sprawl by saying no, with evidence, to tools that do not change what the organisation can do.
• Own the AI developer tooling estate end to end and hand graduated platforms over with a working operating model.

What you'll need

• 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, including how they are licensed, entitled, supported and adopted at scale.
• Strong working knowledge of at least one part of the pharma value chain.
• Solid technical fluency in modern AI/ML, including LLMs, agentic systems, AI agents and workers, ML lifecycle, and data and evaluation patterns, sufficient 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 covering discovery, opportunity sizing, roadmap shaping, prototyping and stakeholder alignment, ideally on products whose core behaviour is AI rather than conventional software.

Nice to have

• Hands on with the AI platform ecosystem as a daily practitioner, fluent in how the landscape is categorised and which capabilities are genuinely distinct.
• Able to evaluate from first principles and design the evaluation itself, defending the method to engineers and vendors alike.
• A proven record of retiring and consolidating technology, including at least one tool killed on evidence.

Details

• Location: Bengaluru, Luxor North Tower.