Scaled AI Success Engineer

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The AI Success Engineer role is the primary post-sales point of contact for important customers, responsible for driving account health and adoption, ensuring technical readiness, and delivering measurable value with OpenAI’s platform.

Responsibilities:

• 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

Requirements:

• 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