Principal (Senior Director), AI Product Management (HR Operations, Talent, and Rewards)

Business Introduction

GSK remains committed to achieving bold commercial ambitions for the future. By 2031, we aim to deliver £40 billion in annual sales, leveraging our existing strong performance momentum to significantly increase our positive impact on the health of billions of patients globally. Our Ahead Together strategy is centered on early intervention to prevent and alter the course of disease, thereby protecting people and supporting healthcare systems. Our diverse portfolio consists of vaccines, specialty medicines, and general medicines.

Through continuous innovation and a dedicated focus on scientific and technical excellence, we strive to develop and launch new, groundbreaking treatments that address critical health challenges.

Position Summary

GSK's Enterprise AI team exists to translate the promise of AI into measurable impact across every major group at GSK — R&D, Medical, Commercial, Supply Chain, HR, Legal, Finance, and beyond. You will act as the strategic compass for driving a portfolio of AI solutions that transform HR Operations across the globe — from onboarding and employee data management through HR service delivery, payroll inputs, leave and absence, and offboarding — and own the forward deployed strategy each pod executes against.

This is a senior individual contributor role for someone who can see across GSK's value chain, identify where AI will create disproportionate value, prototype hands on, and ensure engineers are always deployed against the highest-impact opportunities. You will not manage engineers; you will shape what they build, where they go next, and how we measure whether it worked. Forward deployed teams are most powerful when paired with sharp opportunity selection: you will identify, size, and prioritize the AI opportunities that matter most to GSK, pressure-test proposed engagements against value, feasibility, and strategic fit, and build the case, framing, prototype, and executive alignment needed for the pod to land and scale — while ensuring AI improves, rather than degrades, the employee experience.

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 the hire-to-retire lifecycle — onboarding, employee data management, HR service delivery and case management, payroll inputs, leave and absence, and offboarding — and develop a global portfolio of AI products ranked by impact, feasibility, and time-to-value.

• Quantify value rigorously by building business cases that hold up with finance and executive sponsors — cost-to-serve, service levels, cycle time, case deflection, and employee experience.

• Develop domain pattern recognition in HR Operations workflows — including how work actually flows between HR shared services, HR business partners (HRBPs), and employees — so you can spot AI-shaped problems the business itself hasn't 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 won't move scalable outcomes, protecting engineering focus.

• Be the strategic counterpart to the forward deployed, full-stack, and data 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.

• Design the human-digital split, deciding which tasks the pod's digital workers own — across self-service, the service center, and centers of expertise — where engineers and business users stay in the loop, and how evaluation and oversight make that safe.

• Design AI that is deployable, not just possible, building employee data privacy (GDPR and local equivalents), works council consultation, EU AI Act requirements for high-risk employment-related AI, and bias testing across employee groups into every solution.

• Operate fluently with senior HR leaders, including the CHRO leadership team, HR Operations heads, and center-of-expertise leads, running executive conversations that turn HR transformation priorities into concrete, fundable AI engagements and driving adoption across a global, multi-country workforce.

• 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 didn't, 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 doesn't.

Why You?

Basic Qualification

We are seeking professionals with the following required skills and qualifications to help us achieve our goals

• 15 or more years of professional experience across some combination of pharma/life sciences, AI/ML product strategy, and product management or strategy roles in technology-led organizations.

• Track record of taking at least one technology or AI initiative from problem framing through executive funding and into delivery.

• Direct involvement in HR Operations, including at least one of: onboarding, employee data management, HR service delivery and case management, payroll inputs, leave and absence, or offboarding.

• Hands-on work with modern AI/ML concepts — including LLMs, agentic systems, and digital workers, the ML lifecycle, and data and evaluation patterns — demonstrated through prototyping.

• Prior responsibility for operating as an individual contributor without direct reports and influencing engineering and business teams through frameworks and documented decision criteria.

• Background in product management or product strategy, including opportunity sizing, roadmap development, prototyping, and stakeholder alignment.

• Working knowledge of the HR technology and data landscape, such as Workday, SAP, or a comparable HR system, and case management and knowledge platforms — including the quality, ownership, and integration issues in employee data, enough to judge quickly whether an AI use case is ready to build or blocked by data.

• Direct involvement in HR service delivery operating models, including tiered service models (self-service, service center, centers of expertise), service-level and cost-to-serve measures, and where automation and AI can take on work without degrading the employee experience.

• Working knowledge of the regulatory and ethical constraints on AI in HR, including employee data privacy (GDPR and local equivalents), works council consultation, the EU AI Act's high-risk classification for employment-related AI, and bias testing across groups of employees.

• Direct involvement in partnering with senior HR leadership to turn HR transformation priorities into funded, measurable programs, and in driving adoption across a global, multi-country workforce.

Preferred Qualification

If you have the following characteristics, it would be a plus

• Prior experience in forward deployed engineering, app