ChatGPT is a rapidly evolving system: new capabilities ship continuously, product surfaces change quickly, and usage patterns shift week-to-week. Supporting that pace requires infrastructure that can handle real production constraints—high concurrency, unpredictable traffic patterns, complex dependency graphs, and frequent change. The job of ChatGPT Infrastructure is to build and operate the platforms that make fast iteration possible without breaking performance or reliability. We design the shared systems, data paths, rollout mechanisms, and reliability guardrails that teams rely on when shipping changes to ChatGPT at scale. We focus on high-leverage infrastructure: primitives and “golden paths” that turn hard-won operational lessons into defaults—so engineers don’t need to rediscover the same failure modes, latency pitfalls, or integration issues each time they build something new. We’re hiring Senior and Staff engineers to design and build infrastructure systems that sit underneath ChatGPT and multiply the effectiveness of the teams building user experiences. This is not a “keep the lights on” role. It’s a platform-building role: you’ll define interfaces, develop core abstractions, and create tooling that makes safe, fast iteration the norm. Your work will show up as less friction, fewer regressions, better performance, and systems that scale gracefully as the product expands. You might work on one or more of these areas (without being locked into any single lane): Platform foundations & frameworks: core libraries, service frameworks, and shared components that standardize how systems are built, integrated, and evolved. Scalability & performance primitives: patterns and infrastructure that reduce tail latency, improve throughput, and keep costs predictable as demand grows. Reliability guardrails: mechanisms that prevent outages by design—rate limiting, load shedding, dependency isolation, backpressure, safe fallbacks, and “make it hard to regress” controls. Developer productivity via golden paths: paved roads for common workflows (data access patterns, service integration patterns, request lifecycle patterns) that are fast, safe, and easy to use. Observability & debugging systems: instrumentation, metrics models, and investigative tooling that turn “it’s slow” into a precise, actionable diagnosis. Safe change management: deployment and rollout systems that support rapid iteration with confidence—progressive delivery, automated verification, and fast rollback strategies. Interface and contract design across boundaries: clean APIs and stable contracts that reduce coupling and allow independent evolution across a complex ecosystem.
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Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed