Sr. AI Product Manager – Market Access

GSK•Philadelphia, PA

2d•Hybrid

About The Position

The Sr. AI Product Manager will lead how GSK applies AI to deliver measurable commercial outcomes across Market Access. Areas include enterprise and provider account management, pricing and contracting, trade and channel management, and payer engagement. The role works closely with business leaders to identify high-value opportunities, determine feasibility and build-versus-buy approaches, and own delivery from discovery through production deployment and ongoing performance management. The position sits at the intersection of product, engineering, and commercial strategy. It leads teams and vendors through solution design, development, evaluation, and deployment, integrating AI capabilities with commercial systems such as CRM and account platforms, contract and rebate management systems, and cloud data platforms. The role defines quality and performance expectations for non-deterministic AI systems and ensures solutions are governed, monitored, and responsibly used in production. Success is measured by adoption and quantified commercial impact. This is a hybrid position, with on-site work part of the week and remote work the remainder.

Requirements

At least 8 years of experience in life sciences or healthcare, including market access commercial operations such as enterprise or provider account management, pricing, contracting, trade and channel management, or payer engagement.
Experience translating complex business problems into programs with measurable results.
Experience setting priorities and developing roadmaps or investment cases for senior leadership decisions.
Experience overseeing technology delivery from design through production deployment on commercial platforms such as CRM/account management, contract and rebate management, or trade data and master data management.
Experience managing delivery teams and vendors on complex programs, including budgets, timelines, and quality.
Experience building and operating agentic AI or LLM-based workflows in production environments, from concept through measured outcome.
Experience with market access commercial systems, including enterprise CRM and account platforms; contract, chargeback, rebate, and gross-to-net systems; trade data and wholesaler/distributor feeds; formulary and claims data; and customer/account master data.
Experience with agile delivery and testing or validation in regulated environments, including computer system validation and SOX/GxP-aligned change control.
Experience partnering with data scientists and vendors on evaluation, monitoring, and governance of models and agentic workflows.
Experience presenting complex information to senior stakeholders.
Bachelor's degree in business, economics, data science, computer science, public health, or life sciences.

Nice To Haves

Advanced degree (MBA, MSc, MPH, or PhD) in a relevant discipline.
Direct experience building AI solutions for market access operations, enterprise or provider account intelligence, contract and trade analytics, real-world evidence, or health technology assessment.
Experience with IDN/health system affiliation data and account hierarchy modeling, and with 340B, specialty pharmacy, and distributor channel data and compliance.
Experience designing or operating agentic AI or automation platforms in a regulated enterprise setting.
Familiarity with cloud AI platforms, data platforms such as Snowflake or Databricks, integration of AI with Salesforce or Veeva, and MLOps/LLMOps concepts.
Experience with human-in-the-loop systems, prompt engineering, or deploying generative AI in regulated environments.
Experience assessing AI vendors or platforms.
Experience leading transformation, merger integration, or operating model change.
Experience with AI or advanced analytics solutions.

Responsibilities

Identify and prioritize AI and agentic technology opportunities across account management, organized provider systems, pricing, contracting, chargebacks and rebates, trade and channel management, and payer engagement, weighing impact, feasibility, and risk.
Shape the AI roadmap, balancing near-term opportunities with long-term capabilities, and evaluate build, buy, and partner options.
Partner with Market Access, Commercial Operations, Trade & Distribution, Finance, Technology, and Data teams to translate business needs into clear problem statements.
Develop business cases that define expected benefits, costs, and success measures.
Lead end-to-end delivery, directing data scientists, engineers, UX designers, and vendors through design, development, evaluation, and production deployment, including integration with commercial and data platforms.
Partner with Data Engineering and commercial data owners to establish the data quality, lineage, and master data alignment required for AI products.
Set quality standards for AI solutions; validate before release and monitor model, prompt, and agent performance after launch; manage versioning and change control; triage failures and drift; and run continuous improvement based on user feedback.
Build responsible AI practices into solutions, including human oversight, documentation, compliance, governance, GxP/SOX-relevant controls, government pricing and 340B compliance, privacy, and auditability.
Manage budgets, timelines, vendor performance, and delivery risks, escalating issues early.
Prototype and validate solutions with account teams and contracting, trade, and channel operations users; drive adoption through enablement, training, documentation, and SOP updates; and develop reusable patterns for other Commercial and D&T teams.