Staff (Director), Commercial Enterprise Product Mgmt. - E2E Marketing Enablement

GSK • Enterprise AI About the Role GSK’s Enterprise AI team, a highly skilled applied AI group, translates the promise of AI into measurable impact across every major group at GSK — R&D, Medical, Commercial, Supply Chain, HR, Legal, Finance, and beyond. Bionic pods — AI product managers, forward deployed engineers, full-stack engineers, data engineers, and digital workers — embed directly with scientific and business teams to build AI products that change outcomes. We are hiring a Staff, Marketing Automation & AI Product Manager to own a major slice of our marketing enablement opportunity portfolio — marketing automation, content supply chain and assembly, the marketing experience layer, campaign management, and performance measurement and act as the strategic counterpart to the engineers and digital workers in your pod, setting the forward deployed strategy they execute against. This is a senior individual contributor role for someone who can identify and shape high-value AI opportunities within marketing enablement, build the case to fund and deploy against them, and ensure FDEs are working on what matters most. You will not manage engineers; you will shape what they build in your domain and how we measure whether it worked. Why This Role Exists Forward deployed teams are most powerful when paired with sharp opportunity selection. Enterprise AI has no separate strategy layer: the AI Product Manager sets the forward deployed strategy, and the pod executes it. This role closes that gap at this level by ensuring the engineers we deploy are working on the right things. In this role you will be the person who: • Owns a clear domain or capability area within the Enterprise AI opportunity portfolio. • Identifies, sizes, and shapes the highest-value AI opportunities in that domain. • Partners daily with forward deployed, full-stack, and data engineering leads to scope and steer engagements end-to-end. • Builds the business and executive alignment the pod needs to land and scale. How This Differs from Traditional Product Management This is not a traditional enterprise product role managing a source system’s roadmap, releases, and backlog. As an AI Product Manager in Enterprise AI, you: • Build new AI products from ambiguous, unsolved business problems rather than evolving an established platform. • Work with probabilistic systems — defining evaluations, acceptable error, and human oversight instead of fixed functional requirements. • Help lead a bionic pod, deciding which work goes to engineers and which to digital workers, and how they hand off. • Prototype hands on and are measured on business outcomes, not features shipped or system uptime. Key Responsibilities Opportunity Identification & Value Sizing • Hunt for high-value AI opportunities across marketing automation, content supply chain and assembly, the marketing experience layer, campaign management, and performance measurement; develop a structured pipeline of opportunities ranked by impact, feasibility, and time-to-value. • Quantify value rigorously. Build credible business cases that survive finance and senior business unit scrutiny — 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 marketing enablement workflows the business itself hasn’t yet articulated. Strategic Prioritization & Portfolio Shaping • Shape the opportunity portfolio in your domain. Maintain a living view of in-flight, queued, and de-prioritized opportunities, with the rationale for each decision, and feed it into the broader Enterprise AI portfolio. • Make trade-off recommendations. When two business sponsors both want an FDE pod, defines the success metrics,