Staff, AI Product Manager

Job Purpose: 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. • Work with probabilistic systems, defining evaluations, acceptable error, and human oversight. • Help lead a bionic pod, deciding which work goes to engineers and which to AI agents and workers, and how they hand off. Prototype hands on and are measured on business outcomes • Owns the Orchestration and Automation platform tower and its roadmap. • Takes consolidation decisions across the low and medium code platform estate. • Acts as the platform consultant for business teams building on the estate. Owns the governance model that defines what a citizen developer may build unsupervised Responsibilities : Platform Portfolio & Consolidation • Map capability against actual usage across the whole low and medium code estate, and recommend what consolidates, what stays, and what retires. • Quantify value rigorously. Build credible business cases that survive finance and senior business unit scrutiny — cycle time saved, manual effort removed, licence cost avoided, automations running in production. • Develop deep automation pattern recognition so you can spot the workflows worth automating and the ones that should be fixed at source instead. Strategic Prioritization & Portfolio Shaping • Shape the platform roadmap. Maintain a living view of in-flight, queued, and de-prioritized platform work, with the rationale for each decision, and feed it into the broader AI Platforms & Tools portfolio. • Make trade-off recommendations. When two business sponsors both want platform investment, define the success metrics, run the analysis, and recommend where effort goes. • Protect engineering focus. Push back — with evidence — on opportunities that won’t move scalable outcomes. Required Skills: • 16+ years of progressive experience in enterprise platform leadership, with a meaningful part of it spent owning a platform or platform estate end to end: roadmap, architecture direction, operations, and lifecycle. • Demonstrated track record of taking a platform from fragmented or underused to well run: consolidation calls made, adoption grown, and the operating model that sustained it. • Experience running a platform in a regulated enterprise, with working knowledge of at least one part of the pharma value chain and the data, decisions, and constraints inside it. • Solid technical fluency in modern AI/ML, covering LLMs, agentic systems, AI agents and workers, data and evaluation patterns, sufficient to set architecture direction, challenge engineers, scope realistically, and avoid hype-driven choices. • Experience leading engineers directly while also leading a far larger citizen developer community through influence, frameworks, and quality of thinking. • A platform product heritage: roadmap shaping, lifecycle and version management, vendor and licensing ownership, service levels, and stakeholder alignment across a large and varied user base. Preferred skills : • Deep, hands-on Microsoft Power Platform experience is mandatory: Power Apps, Power Automate and Dataverse at enterprise scale, including environment strategy, ALM, licensing, and the governance model around them. • Has owned a low or medium code automation platform at enterprise scale and run a citizen developer or self-service programme covering thousands of users, with guardrails that held under pressure. • Fluent with the wider low and medium code agent and workflow stacks that sit alongside Power Platform, such as Copilot Studio, n8n, and the equivalents from the major cloud vendo