Dedicated Support Engineering Lead

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. Within Premium Support, Dedicated Support Engineers combine deep technical troubleshooting with an enduring understanding of our most strategic customers’ architectures, critical workloads, and business priorities. Through proactive reliability work, ownership during incidents, and AI-powered support capabilities, we help customers operate successfully as their use of OpenAI grows. About the Role We’re looking for a senior leader to build and scale our Dedicated Support Engineering function globally. You will define its strategy, build the team, and establish how we deliver technically rigorous, proactive support for customers running some of the most complex and consequential workloads on OpenAI. This role combines organizational leadership, technical judgment, and executive customer engagement. You will establish a model in which DSEs develop deep customer context, independently advance difficult investigations, anticipate operational risks, and drive issues through resolution. You will also turn what the team learns into improvements that benefit customers across OpenAI. You should bring experience building technical organizations that maintain long-term accountability for enterprise customers. Leadership in Technical Account Management, enterprise Support Engineering, or a comparable technical customer function is particularly relevant. Success requires a strong foundation in production troubleshooting and reliability, alongside the ability to build trusted relationships with customer engineering leaders and executives. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role you will... - Set the strategy for Dedicated Support Engineering. Define the function’s charter, service model, priorities, and growth plan. Translate customer needs and company priorities into clear decisions about where to invest and how to scale. - Build and develop a high-performing global organization. Hire and coach senior technical talent, develop future leaders, and establish expectations for technical depth, customer ownership, collaboration, and performance. - Design the customer engagement model. Establish how DSEs are assigned to customers, build account knowledge, conduct operational reviews, and prepare for critical events. Define clear responsibilities and handoffs with Support, Technical Success, Sales, and Engineering. - Set the standard for technical ownership. Ensure the team uses evidence, reproduction, and systems-level investigation to advance complex issues. Develop the team’s judgment on when to continue investigating, mitigate, or engage Engineering, and stay close enough to the work to guide difficult decisions. - Build proactive reliability into the service. Establish practices for assessing customer architectures and dependencies, identifying emerging risks, and preparing for launches, migrations, and traffic growth. Ensure incident learnings lead to completed corrective actions. - Lead through critical customer situations. Serve as a senior escalation point, align responders across teams, and communicate clearly with customer executives. Maintain accountability for the customer’s support experience through mitigation, resolution, and follow-through. - Own delivery quality and sustainable growth. Build capacity plans, coverage arrangements, and investment proposals that support service commitments. Balance customer complexity, team workload, and time for proactive work as the customer portfolio grows. - Define and measure meaningful outcomes. Establish measures of investigation quality, time to mitigation, recurring issue reduction, customer confidence, and proactive risk reduction. Use these insights to improve the service and guide investment. - Influence product and engineering priorities. Turn patterns across customer investigations into evidence-backed recommendations. Build alignment with senior partners on reliability, observability, supportability, and tooling improvements. - Make AI and automation foundational to the function. Apply OpenAI’s technology to preserve customer context, accelerate investigations, detect risks, and automate repeatable work. Establish evaluations and human oversight so these capabilities improve quality and customer trust

Set the strategy for Dedicated Support Engineering. Define the function’s charter, service model, priorities, and growth plan. Translate customer needs and company priorities into clear decisions about where to invest and how to scale. Build and develop a high-performing global organization. Hire and coach senior technical talent, develop future leaders, and establish expectations for technical depth, customer ownership, collaboration, and performance. Design the customer engagement model. Establish how DSEs are assigned to customers, build account knowledge, conduct operational reviews, and prepare for critical events. Define clear responsibilities and handoffs with Support, Technical Success, Sales, and Engineering. Set the standard for technical ownership. Ensure the team uses evidence, reproduction, and systems-level investigation to advance complex issues. Develop the team’s judgment on when to continue investigating, mitigate, or engage Engineering, and stay close enough to the work to guide difficult decisions. Build proactive reliability into the service. Establish practices for assessing customer architectures and dependencies, identifying emerging risks, and preparing for launches, migrations, and traffic growth. Ensure incident learnings lead to completed corrective actions. Lead through critical customer situations. Serve as a senior escalation point, align responders across teams, and communicate clearly with customer executives. Maintain accountability for the customer’s support experience through mitigation, resolution, and follow-through. Own delivery quality and sustainable growth. Build capacity plans, coverage arrangements, and investment proposals that support service commitments. Balance customer complexity, team workload, and time for proactive work as the customer portfolio grows. Define and measure meaningful outcomes. Establish measures of investigation quality, time to mitigation, recurring issue reduction, customer confidence, and proactive risk reduction. Use these insights to improve the service and guide investment. Influence product and engineering priorities. Turn patterns across customer investigations into evidence-backed recommendations. Build alignment with senior partners on reliability, observability, supportability, and tooling improvements. Make AI and automation foundational to the function. Apply OpenAI’s technology to preserve customer context, accelerate investigations, detect risks, and automate repeatable work. Establish evaluations and human oversight so these capabilities improve quality and customer trust.