Head of Strategic Execution

OpenAI
San FranciscoPosted 19 March 2026

Job Description

Head of Strategic Execution ABOUT THE TEAM OpenAI’s enterprise customers are making significant investments in AI, and adoption is accelerating. But meaningful AI transformation is not just a technology rollout, it reshapes how organizations operate, make decisions, and create value. The AI Strategy & Adoption team partners with OpenAI’s most strategic enterprise customers to guide them through that transformation. We work directly with executive leaders to translate frontier AI capabilities into new operating models, workforce transformation, and measurable business outcomes. Our mission is to help organizations move from AI experimentation to sustained enterprise capability, enabling them to continuously innovate and reinvent their business. ABOUT THE ROLE - We are seeking a senior leader with experience designing and facilitating high-impact executive journeys that turn complexity into clarity, alignment, and momentum. - In this role, you will work alongside the Head of AI Strategy & Adoption to design and deliver the experience environments through which OpenAI engages enterprise leaders in AI transformation. This role will help shape how OpenAI partners with enterprise leadership teams to understand and act on the implications of frontier AI. - You will architect the human interactions, workshops, and structured moments through which executive teams explore the implications of AI and align on a transformation roadmap. You will also help design the AI-native methods, tools, and digital layers that make these experiences more insightful, participatory, adaptive, and scalable. - Your role is to ensure these engagements are strategically sound, experientially powerful, and increasingly powered by the capabilities OpenAI brings to market. IN THIS ROLE, YOU WILL - Design and lead executive engagements, immersive sessions, workshops, and transformation experiences for OpenAI’s most strategic enterprise customers, using AI-native methods to improve preparation, personalization, participation, synthesis, and follow-through. - Translate frontier AI capabilities into clear, compelling, and decision-ready experiences for senior leaders. - Model AI-native ways of working for both customers and internal teams, demonstrating how frontier models can enhance strategic preparation, workshop design, live facilitation, synthesis, and action planning. - Facilitate high-stakes conversations with executive leadership teams that help organizations move from ambiguity to alignment on vision, priorities, measures of success, and roadmaps. These engagements support commitment to execution and enable a formalized handoff to Strategic Execution. - Partner with senior leaders to establish measures of success and initial accountability for transformation initiatives. - Architect the end-to-end customer journey across key moments of the AI Strategy & Adoption motion, including LEAP and future engagement models. - Define and evolve repeatable experience frameworks, formats, and standards that scale OpenAI’s enterprise transformation work while maintaining depth and quality. - Partner closely with Executive Engagement and Strategic Execution leads to ensure strategic narrative, experiential design, and execution remain tightly integrated. - Help shape the digital and application layer behind the motion, ensuring tools and platforms enhance executive understanding, participation, and follow-through. - Help define and evolve OpenAI’s enterprise transformation methodology through insights generated from executive engagements. - As this motion evolves, this role may also help build and mentor a small team responsible for scaling executive engagement experiences. YOU’LL THRIVE IN THIS ROLE IF YOU - Use AI fluently in your own work and see frontier models not just as content tools, but as design material for new kinds of executive experiences. - Can imagine and prototype AI-powered experiences that go beyond traditional workshops and pre ... (truncated, view full listing at source)
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