Principal Program Manager - AI Strategy

We are seeking a Principal Program Manager to lead enterprise-wide AI strategy and transformation at scale. In this role, you will be the single-threaded owner of a multi-org AI adoption program, responsible for defining the vision, building the operating model, and driving measurable productivity impact through AI-powered automation and GenAI tool integration across a workforce of thousands. You will operate as a strategic leader at the intersection of AI product adoption, operational transformation, and organizational change management. This role requires you to stitch together a fragmented landscape of AI experiments, 1P/3P tools, and automation initiatives into a coherent strategy — setting priorities, building coalitions across VP-level organizations, and creating the measurement frameworks that demonstrate AI's business impact. You will build and lead a federated program model spanning multiple working groups, influence without authority across senior leadership, and serve as the connective tissue between engineering/product teams building AI capabilities and the operational organizations adopting them. This is not a role for someone who simply tracks projects — it requires a strategic thinker who can shape the "how" and "what" of AI transformation, navigate ambiguity, and drive organizational alignment at scale. Key job responsibilities Define and own the end-to-end AI transformation strategy, roadmap, and operating model across multiple VP-level organizations

• Build and lead a federated program structure (working groups, SPOCs, steering committees) that drives accountability while respecting distributed ownership
• Design productivity measurement frameworks that quantify AI's impact — including throughput metrics, complexity weighting, automation categorization, and baseline methodology Orchestrate the AI experimentation portfolio — connecting teams working on similar use cases, prioritizing investments, recommending scaling vs. sunset decisions, and synthesizing learnings
• Drive 1P AI platform adoption strategy, identifying high-impact use cases, removing adoption barriers, and partnering with product teams to shape tool roadmaps
• Lead executive communication — translating complex operational and AI impact data into compelling narratives for VP+ leadership through MBRs, QBRs, and strategic planning cycles
• Establish the governance model for AI experimentation including security review pathways, responsible AI guardrails, and scaling criteria
• Partner with analytics and data science teams to build dashboards and tracking mechanisms that provide real-time visibility into AI-driven efficiency gains Inform annual planning (OP1/OP2) by synthesizing experiment outcomes, common problem statements, and solution extensibility into resource and investment recommendations
• Serve as the cross-org "air traffic controller" — maintaining a bird's-eye view of all AI initiatives, identifying duplication, driving reuse, and ensuring initiatives sum to program-level goals