Scaled AI Success Engineer

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 f