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.
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/backpressure, 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 shedding, rate limiting, and fault isolation.
Experience building systems for safe iteration: progressive delivery, correctness checks, automated rollout gates, and production validation.
Strong instincts for API and contract design—how to create interfaces that are stable, evolvable, and hard to misuse.
Prior work that demonstrates “force multiplier” impact: enabling many teams through a small number of well-chosen primitives.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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