Software Engineer, ChatGPT Infrastructure

About the Team

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, back pressure, 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.

• Build and evolve infrastructure platforms that many engineers and services depend on.

• Translate messy real-world constraints into clean abstractions: simple APIs, enforceable contracts, safe defaults.

• Drive improvements in reliability and performance through principled design, measurement, and iterative hardening.

• Partner across engineering and product to identify systemic pain points and turn them into reusable solutions.

• Own outcomes end-to-end: design → implementation → rollout → operational maturity.

• Experience building and operating large-scale distributed systems in production (high throughput, concurrency, and failure handling).

• Strong fundamentals in systems design, including caching, consistency, queueing/back pressure, and resilient dependency management.

• Ability to reason about performance (latency distributions, tail behavior, bottlenecks) and translate that into concrete engineering work.

• Track record of building platforms or shared infrastructure that improves velocity and correctness for other teams.

• Strong communication and collaboration skills—aligning on interfaces, navigating tradeoffs, and driving cross-team execution.

• Experience designing paved roads / golden paths (frameworks, libraries, self-serve tooling) that shape engineering behavior at scale.

• Deep understanding of reliability techniques: graceful degradation, circuit breakers, load…