OpenAI
Dedicated Support Engineer - London
- Employment type
- Full-time
- Workplace type
- Hybrid
- Location
- London, UK
- Published
- Oct 3, 2026
- Last checked
- Oct 26, 2026
About this role
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.
About the Role
The Support Engineering team works closely with Engineering, Product, Technical Success, Go-to-Market, and other teams to deliver an exceptional experience for our most strategic customers. We combine deep technical troubleshooting with durable customer context, proactive reliability work, and clear ownership during critical moments. We use automation, agents, and our own technology to help build the future of technical support.
We’re looking for experienced, deeply curious technical problem-solvers to serve as trusted support partners for our Premium Support customers. You’ll work directly with customers on novel, ambiguous, and high-impact technical issues, using logs, telemetry, reproduction, and systems-level investigation to isolate causes and drive issues toward resolution.
Beyond resolving individual issues, you’ll use your deep understanding of OpenAI’s infrastructure and products, together with each customer’s architecture and operating context, to anticipate risk and make their workloads more resilient over time. You’ll proactively monitor integrations, identify emerging failure patterns and architectural breakpoints, and work with customers and internal teams to address them before they become incidents. Success means that as a customer’s workloads mature and scale, the day-to-day effort required to support them decreases through better monitoring, runbooks, automation, and preventative improvements.