Principal, AI Product Manager

Position Summary

GSK's Enterprise AI team exists to translate the promise of AI into measurable impact across drug discovery, development, manufacturing, and commercial. You will lead that effort for GSK's Global Supply Chain (GSC) Business Unit, acting as the strategic compass for where AI can create the greatest impact and ensuring that value is actually realized. You will identify where AI will create disproportionate value and keep teams focused on the highest-impact opportunities at all times - defining and agreeing the AI strategy and roadmap for part of GSC in partnership with senior business stakeholders, and prioritizing opportunities based on feasibility and value.

You will line manage a team of Product Managers, oversee third-party contractors, and shape what the technical teams build and where they go next to deliver the highest-impact products, while partnering with GSC peers leading AI across Quality, Manufacturing Engineering, Supply Chain Network Strategy, and CMC to identify cross-functional opportunities and drive consistent, reusable technology and approaches. Forward deployed teams are most powerful when paired with sharp opportunity selection; this role closes that gap - pressure-testing proposed engagements against value, feasibility, and strategic fit, and building the case, framing, prototype, and executive alignment needed for engineers to land and scale.

Responsibilities

This role will provide you the opportunity to lead key activities to progress your career. These responsibilities include some of the following:

• Hunt for high-value AI opportunities across RD, 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 so you can spot AI-shaped problems in scientific and operational workflows that the business itself hasnt yet articulated.
• Own the Enterprise AI opportunity portfolio, maintaining a living view of in-flight, queued, and de-prioritized opportunities, with the rationale for each decision.
• Make hard trade-off calls -building the framework, defining success metrics, running the analysis, and recommending where engineers go when business units compete for the same resources.
• Say no, with evidence, to opportunities that look attractive but wont move scalable outcomes, protecting engineering focus.
• 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.
• Surface re-use and platform leverage, spotting when a one-off solution should become a reusable capability and working with engineering to make that case.
• Operate fluently with senior business and scientific leaders, running executive conversations that turn fuzzy ambitions into concrete, fundable AI engagements.
• Build sponsor coalitions, securing the air cover, data access, and change-management commitment that engineering deployments require to succeed.
• Communicate impact clearly, telling the value story to ELT and the board, in language that connects AI work back to patients, science, and shareholder outcomes.
• 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 didnt, and feeding those learnings back into opportunity selection and engagement design.
• Continuously sharpen the investment thesis on where AI most belongs at GSK, and where it doesnt.

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 RD, 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.

Skills

• AI Platforms
• Product Roadmapping
• Product Delivery
• Change Management
• Data Analysis
• ML Platforms
• Model Evaluation
• Machine Learning Model Management
• Feature Prioritization