Principal Program Manager - AI Strategy

Amazon Amazon · Big Tech · Irving, TX · Project/Program/Product Management--Non-Tech

This role is for a Principal Program Manager focused on enterprise-wide AI strategy and transformation. The individual will lead a multi-org AI adoption program, defining vision, building operating models, and driving productivity impact through AI/GenAI integration. Responsibilities include strategic leadership, program management, defining measurement frameworks, orchestrating experimentation, driving platform adoption, executive communication, establishing governance, and partnering with data teams. The role emphasizes shaping AI transformation, navigating ambiguity, and driving organizational alignment.

What you'd actually do

  1. Define and own the end-to-end AI transformation strategy, roadmap, and operating model across multiple VP-level organizations
  2. Build and lead a federated program structure (working groups, SPOCs, steering committees) that drives accountability while respecting distributed ownership
  3. Design productivity measurement frameworks that quantify AI's impact — including throughput metrics, complexity weighting, automation categorization, and baseline methodology
  4. Orchestrate the AI experimentation portfolio — connecting teams working on similar use cases, prioritizing investments, recommending scaling vs. sunset decisions, and synthesizing learnings
  5. Drive 1P AI control adoption strategy, identifying high-impact use cases, removing adoption barriers, and partnering with product teams to shape tool roadmaps

Skills

Required

  • 7+ years of working cross functionally with tech and non-tech teams experience
  • 7+ years of program or project management experience
  • 7+ years of managing, analyzing and communicating results to senior leadership experience
  • Bachelor's degree
  • Experience implementing repeatable processes and driving automation or standardization
  • Experience defining program requirements and using data and metrics to determine improvements

Nice to have

  • Experience delivering projects within scope, time, budget and quality
  • Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
  • Experience identifying opportunities to integrate AI solutions into products and services to drive business value.

What the JD emphasized

  • single-threaded owner
  • multi-org AI adoption program
  • workforce of thousands
  • AI product adoption, operational transformation, and organizational change management
  • stitch together a fragmented landscape of AI experiments, 1P/3P tools, and automation initiatives into a coherent strategy
  • building coalitions across VP-level organizations
  • measurement frameworks that demonstrate AI's business impact
  • federated program model spanning multiple working groups
  • influence without authority across senior leadership
  • connective tissue between engineering/product teams building AI capabilities and the operational organizations adopting them
  • not a role for someone who simply tracks projects
  • strategic thinker who can shape the "how" and "what" of AI transformation
  • navigate ambiguity
  • drive organizational alignment at scale
  • 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