Principal, AI Product Manager
About the role
Position Summary
Responsibilities
Hunt for high-value AI opportunities
across R&D, global supply chain, and commercial functions; develop a structured pipeline of opportunities ranked by impact, feasibility, and time-to-value.
- Build credible business cases that hold up with finance and executive sponsors - cycle time saved, decisions accelerated, revenue uplift, cost avoided, scientific productivity gained.
•
Develop deep domain pattern recognition
Own the Enterprise AI opportunity portfolio,
Make hard trade-off calls —
Say no, with evidence,
Be the strategic counterpart to the FDE and full-stack engineering leads,
translating ambiguous business problems into crisp problem statements, prototypes, success metrics, and decision frameworks engineers can build against.
- Shape engagements end-to-end - defining scope, success criteria, exit conditions, and scaling pathways before kick-off, then staying close as engineers execute.
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Surface re-use and platform leverage,
Operate fluently with senior business and scientific leaders,
Build sponsor coalitions,
Communicate impact clearly,
Define how we keep score,
establishing the value-realization framework Enterprise AI uses to measure impact across deployments.
- Run honest post-mortems - capturing what worked, what didn't, and feeding those learnings back into opportunity selection and engagement design.
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Continuously sharpen the investment thesis
Basic Qualification
We are seeking professionals with the following required skills and qualifications to help us achieve our goals
- 15 or more 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 organizations.
- Demonstrated track record of identifying, scoping, prototyping, and shepherding high-value technology or AI initiatives from problem framing through executive funding and into delivery.
- Deep working knowledge of the pharma value chain, ideally with first-hand exposure to R&D, clinical, manufacturing, or commercial environments and the data, decisions, and constraints inside them.
- Strong technical fluency in modern AI/ML - LLMs and agentic systems, 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 and developing a team of product managers - setting direction, building talent, and driving quality of thinking and execution across the team.
- A product management or product-strategy heritage: discovery, opportunity sizing, roadmap shaping, prototyping, and stakeholder alignment at scale.
Preferred Qualification
If you have the following characteristics, it would be a plus
- Prior experience in a forward deployed engineering, applied AI, or AI lab/COE setting at a pharma, healthcare, or comparable regulated enterprise.
- Background in management consulting, value engineering, or corporate strategy with hands-on technology depth.
- Familiarity with the manufacturing and supply chain of medicines or vaccines, including the operational, regulatory, and quality considerations unique to pharmaceutical production.
- Experience navigating GxP, regulatory, and data-governance constraints in pharma AI deployments.
#GSK-LI
Skills
AI Platforms, Change Management, Data Analysis, Feature Prioritization, Machine Learning Model Management, ML Platforms, Model Evaluation, Performance Analysis, Product Delivery, Product Design, Product Lifecycle Management (PLM), Product Roadmapping, Roadmap Development, Statistical Analysis, User Needs Analysis
Uniting science, technology and talent to get ahead of disease together.
Important notice to Employment businesses/ Agencies
Not included in the source posting: about the role, benefits.
Skills
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