About the Team
OpenAI’s AI Success Engineer team partners with the world’s most ambitious organizations to translate cutting edge AI into real business value. We guide customers from first deployment through scaled enterprise adoption. Our work spans technical integration and enablement, workflow transformation, and sustained program and product delivery.
Our customers range from fast growing digital natives to the largest global enterprises, government agencies, and educational institutions. Every engagement is an opportunity to shape how AI changes work, productivity, and innovation. This role sits at the center of that mission.
About the Role
The AI Success Engineer role is the primary post-sales point of contact for OpenAI’s most important customers. You are responsible for driving account health and adoption, ensuring technical readiness, identifying new use cases, and delivering measurable value to our customers with OpenAI’s ambitiously growing platform.
This role blends technical depth, program management, customer advisory, and product influence. You will partner deeply with customer teams, map workflows, lead configuration, oversee deployment plans, and guide customers toward high impact use cases that showcase the full value of our platform.
You will work closely with Sales, Solutions Architecture, Product, and Research to ensure the customer experience is connected and successful across every touchpoint. Success in this role means accelerating adoption, increasing customer activation depth, guiding strategic use cases that get to production, and helping customers demonstrate tangible business impact.
In this role, you will:
- Own post-sale technical success, adoption, and value realization across a large portfolio of customers, using customer context, product signals, and business impact to determine where to engage most deeply
- Act as a trusted advisor on deployment health, adoption strategy, and value realization for ChatGPT, API, Codex, and related capabilities
- Use logs, telemetry, usage patterns, and customer feedback to diagnose issues, form hypotheses, and guide practical recommendations on latency, reliability, model choice, prompting, cost efficiency, and rollout readiness
- Lead targeted interventions for moments that matter - launches, risk signals, escalations, renewal preparation, and high-potential expansion opportunities
- Translate customer goals into prioritized adoption plans, success milestones, and measurable KPIs that can be executed through a mix of direct engagement, scaled programs, and cross-functional support
- Conduct technical enablement and configuration guidance, balancing 1:many education and repeatable playbooks with selective 1:1 engagement when the customer moment warrants it
- Identify repeatable use cases, barriers, and adoption patterns across customers, and convert those insights into scaled guidance, interventions, and customer value narratives
- Coordinate cross-functionally with Solutions Architecture, Product, Engineering, Account Directors, User Ops, and Education Programs to keep customer outcomes moving forward
- Know when to go deep independently and when to route or escalate to specialist partners for implementation-heavy or product-specific work
- Build repeatable mechanisms - playbooks, templates, health signals, intervention motions, and reporting - that improve outcomes across the portfolio, not just on one account
- Guide value realization and impact measurement through baselines, KPI definition, and ongoing usage / ROI reporting
- Help drive expansion by identifying where stronger adoption, new workflows, or technical optimization can unlock additional value
You’ll thrive in this role if you:
- 6+ years of experience in technical customer-facing roles such as technical account management, technical success, technical consulting, solutions architecture, technical delivery leadership, or enterprise SaaS / AI adoption
- Strong working knowledge of OpenAI product capabilities, APIs, connectors, and common deployment patterns, and able to explain model behavior, limitations, and tradeoffs in practical business terms
- Technically fluent enough to engage credibly with customer technical teams and interpret logs, telemetry, usage data, and system behavior, without needing to be the primary implementation owner
- Able to reason through production tradeoffs such as latency, cost, quality, prompting, routing, rate limits, retrieval, caching, and reliability, and turn those into practical recommendations
- Comfortable diagnosing adoption or performance challenges using customer conversations, product signals, and technical evidence, then identifying the right next step, owner, or escalation path
- Strong portfolio prioritization instincts and judgment about where direct engagement will create the most customer and business impact
- Excellent project and program management instincts, with the ability to drive multiple workstreams with clarity and structure
- Strong communicator who can move fluidly between executive conversations about business impact and technical conversations about optimization, risks, and constraints
- Operate with high ownership and can manage ambiguity, fast decision making, and dynamic customer needs
- Have a strong record of driving measurable adoption, deployment health, and customer value for large enterprise customers with complex stakeholder environments
- Have experience building repeatable playbooks, processes, or operating mechanisms that scale impact across many customers, not just through individual heroics
- Know when to solve independently and when to pull in Solutions Architecture, Engineering, Product, or other specialist teams
KPIs
- Portfolio adoption and health - improve usage and deployment health across the portfolio, including activation, WAU, feature adoption, token consumption, and other relevant product health indicators
- Intervention effectiveness - identify risk or opportunity signals early and improve outcomes through targeted technical and adoption interventions
- Value realization and expansion influence - document measurable customer value, track progress against KPIs, and help uncover or accelerate new growth opportunities
- Scaled leverage and prioritization - build repeatable playbooks, programs, and intervention mechanisms, while focusing depth where customer impact, risk, and growth potential are highest
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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