Sr. AI Product Manager – Market Access

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 centred 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.


You will lead how GSK uses AI to deliver measurable commercial outcomes across Market Access - spanning enterprise account management, organized provider account systems (IDNs, health systems, ACOs, GPOs, and specialty pharmacy networks), pricing, contracting, trade and channel management (wholesalers, distributors, specialty pharmacies, and 340B), and payer engagement. You will sit with business leaders, understand how their work actually gets done, and decide where AI and agentic technology can make the biggest difference. Then you will own delivery end to end - discovery, build, evaluation, production deployment, and ongoing performance management - working hands-on with agentic frameworks, LLM-based workflows, and the commercial technology stack behind market access (CRM and account platforms, contract and rebate management, trade data, and master data).

This role sits at the intersection of product, engineering, and commercial strategy. You will make your own feasibility and build-vs-buy calls, define what "good" looks like for non-deterministic AI systems, and move solutions from proof-of-concept into governed, monitored production use that integrates with systems of record such as enterprise CRM, contract/chargeback/rebate platforms, and trade data warehouses. Success is measured by adopted capabilities and quantified commercial impact.

We're looking for clear thinkers who combine commercial awareness with practical delivery skills - someone business leaders trust and technologist's respect. This is a chance to shape where GSK invests in AI across market access, in support of our mission to unite science, technology, and talent to get ahead of disease together

Key Responsibilities

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

• Identify where AI and agentic technology can create the most value across enterprise account management, organized provider account systems (e.g., IDN/health system account planning, affiliation and hierarchy mapping, formulary and pathway monitoring), pricing, contracting, chargeback and rebate processing, trade and channel management (wholesaler, distributor, specialty pharmacy, 340B), and payer engagement --- weighing impact, feasibility, and risk to prioritize investment. shape the AI roadmap, balancing quick wins with long-term capability, and assess build, buy, and partner options, including AI capabilities embedded in incumbent platforms versus custom agentic solutions.

• Partner with Market Access, Commercial Operations, Trade & Distribution, Finance, Tech, and Data teams to turn pain points into clear, specific problem statements across enterprise account planning, provider account management, contracting, and channel operations.

• Build business cases with clear expected benefits, costs, and success measures;

• Own delivery end to end - leading data scientists, engineers, UX designers, and vendors through design, build, evaluation, and production deployment, including integration with CRM/account platforms (e.g., Salesforce Life Sciences Cloud, Veeva), contract and rebate management systems (e.g., Model N, Vistex, SAP), and cloud data platforms (e.g., Snowflake, Databricks, Azure) - making key build and release decisions tied back to the business case.

• Partner with Data Engineering and commercial data owners to secure the data foundation these products depend on - contract, pricing, rebate, chargeback, claims, formulary, and trade data (EDI 844/852/867, wholesaler and specialty distributor data, 340B covered entity data) quality, lineage, and master data alignment (customer, account, and organizational hierarchy mastering across HCO/HCP, IDN, GPO, and ship-to/sold-to relationships, e.g., via Reltio, Veeva Network, or IQVIA OneKey).

• Set the quality bar for AI solutions - validate before release, then own them after go-live: monitor model, prompt, and agent performance in production, manage versioning and change control, triage failure cases and drift and run continuous improvement loops from user feedback.

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