Value Engineer, AI Success - San Francisco
OpenAISan FranciscoPosted 17 March 2026
Job Description
Value Engineer, AI Success - San Francisco
About the Team
The AI Success team helps customers turn frontier AI into real business value. We accelerate adoption of OpenAI technology at scale and guide organizations from initial activation to measurable, organization-wide impact. We partner closely with Sales, Product, Solutions Architecture, and Security to deliver safe and responsible AI transformation. Our work shapes how customers generate and measure tangible outcomes from OpenAI products and creates a repeatable blueprint for successful enterprise launches and expansions.
About the Role
We are hiring a Value Engineer to help articulate and quantify the business value of OpenAI’s technology across Enterprise, Education, and Government customers. In this role, you will help customers and internal teams translate AI adoption into measurable financial and operational impact.
As an early member of the Value Engineering team, you will help define how OpenAI measures and communicates the real-world impact of AI across its customers. You will partner closely with Sales, AI Success Engineers, AI Deployment Engineering, and Product teams to identify high-impact AI use cases and build financial and operational business cases. Your work will directly influence executive alignment, investment decisions, renewals, and long-term expansion.
You will play a key role in helping build and shape the value engineering function from the ground up — developing repeatable frameworks, ROI models, value narratives, dashboards, and collateral that help internal teams and customers understand and measure the impact of AI adoption.
Success in this role is measured by how clearly customers and internal teams can quantify the value of AI, how effectively business cases support adoption and expansion, and how scalable value frameworks become across the GTM organization.
This role is based in San Francisco or New York City and we offer relocation benefits to new employees.
In This Role, You Will
- Lead business value assessments for our largest deals, working closely with customers to identify key business drivers and quantify the value of OpenAI’s products to support investment decisions
- Build and maintain standardized ROI, TCO, and value modeling tools for internal and customer use.
- Lead structured value discovery to identify high-impact use cases and define measurable outcomes.
- Publish executive-ready business cases that quantify results and strengthen relationships with C-level stakeholders.
- Codify value frameworks, methodologies, and reusable assets that scale value-based selling across the global GTM organization.
- Establish baselines, KPIs, and dashboards to track and communicate value delivery.
- Partner closely with Account Directors and post-sale teams to influence deal strategy, renewals, and expansion opportunities.
- Contribute to thought leadership on AI-driven business transformation by identifying emerging patterns in how organizations realize value from AI.
You Will Thrive in This Role If You
- Bring 6–10 years of experience in value engineering, management consulting, or adjacent roles.
- Have strong financial and analytical skills, with experience quantifying and presenting value to executive stakeholders.
- Demonstrate exceptional executive presence with strong written, verbal, and presentation skills.
- Have experience working on large-scale AI, cloud, or digital transformation initiatives.
- Communicate with clarity and confidence across technical and business audiences.
- Can translate AI capabilities into compelling financial, productivity, and workforce transformation narratives.
- Enjoy managing multiple complex customers and driving toward concrete, measurable outcomes.
- Demonstrate humility, curiosity, and a customer-first mindset.
- Operate with high ownership, urgency, and comfort navigating ambiguity.
- Are a creative builder who thrives in 0→1 environments and enjoys rolling up your sle ... (truncated, view full listing at source)
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