Software Engineer, ChatGPT Infrastructure
Openai
| Company | Openai |
| Category | Engineering |
| Location | London |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | USD 255k–405k |
| Posted | 28 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
About the Team
Our London-based team builds the backend systems that help ChatGPT scale reliably. We work on infrastructure close to the product, partnering with engineering teams to improve the performance, resilience, and operability of critical user-facing systems.
Our work combines backend software engineering with distributed systems and production reliability. We build shared capabilities, improve high-traffic workflows, and make it easier to introduce new product functionality without compromising performance or availability.
About the Role
This role is for software engineers who want to build and evolve backend systems operating at significant scale. You’ll write production code, design shared infrastructure, and solve technical challenges involving performance, distributed systems, and system reliability.
You’ll also own how those systems behave in production: how changes are rolled out, how issues are detected and diagnosed, and how recurring operational problems can be addressed through better software and system design.
This is a strong fit for backend engineers who enjoy complex systems problems and want a direct connection between the infrastructure they build and the experience of ChatGPT users.
In this role, you will:
- Design, build, and maintain backend systems supporting high-traffic ChatGPT experiences.
- Develop shared services, APIs, and infrastructure that help product teams build and launch new capabilities safely.
- Improve the performance, scalability, and efficiency of production systems as usage and product complexity grow.
- Build and improve systems for asynchronous processing and other large-scale backend workloads.
- Lead architectural improvements and infrastructure migrations while maintaining correctness, compatibility, and safe rollout and rollback.
- Strengthen monitoring, alerting, and diagnostics to detect problems early and reduce customer impact.
- Participate in on-call, incident response, and root-cause analysis, and turn operational learnings into lasting engineering improvements.
- Work across product and infrastructure teams to ensure new systems are reliable, secure, and production-ready.
- Build automation and tooling that reduce repetitive operational work and improve engineering effectiveness.
You might thrive in this role if you:
- Have experience building and operating backend systems at scale.
- Understand distributed systems concepts such as concurrency, consistency, asynchronous processing, and failure handling.
- Enjoy writing production code while taking ownership of how systems behave in real-world conditions.
- Can identify and address bottlenecks affecting latency, throughput, resource usage, or reliability.
- Have experience introducing production changes safely through testing, staged rollouts, monitoring, and rollback plans.
- Are comfortable investigating ambiguous technical problems and collaborating across teams to resolve them.
- Care about clear interfaces, maintainable systems, and practical engineering tradeoffs.
- Take ownership of projects from design and implementation through deployment and ongoing improvement.
Qualifications
- 4+ years of professional software engineering experience, including significant experience building backend or distributed systems.
- Strong proficiency in at least one general-purpose programming language and experience writing reliable, maintainable production code.
- Experience designing, building, or improving services, platforms, or shared infrastructure at scale.
- Familiarity with production reliability practices, including monitoring, incident response, root-cause analysis, and operational readiness.
- Experience diagnosing performance, scalability, or reliability issues in production environments.
- Understanding of distributed systems, data storage, concurrency, asynchronous processing, or networking.
- Familiarity with modern deployment, observability, and
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