The opportunity
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.
What you'll do
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.
What they're looking for
- 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.
