About this role.
OpenAI seeks a senior individual-contributor Performance Engineer to improve latency, throughput, reliability, and cost efficiency for ChatGPT and the developer API. The role spans application, middleware, runtime, and infrastructure performance, including networking, storage, Python runtime, and GPU utilization. Core work includes profiling, instrumentation, observability, benchmarking, root-cause investigation, and architecture-level optimization of distributed production systems. The engineer will partner with infrastructure, platform, training, and product teams to define performance goals, address regressions, and establish latency and throughput SLAs/SLOs. This is a highly autonomous, technically deep position requiring at least seven years of software engineering experience and strong cross-functional influence.
Role DNA
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Job Complexity
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Sample interview questions
I would first validate the regression using comparable traffic windows and break down end-to-end latency by service, endpoint, region, and request characteristic. I would use traces, metrics, profiles, and recent deployment/configuration changes to isolate the dominant contributor, then reproduce the issue under controlled load where possible. After implementing and validating a mitigation, I would add targeted instrumentation and regression tests to prevent recurrence.
I combine resource metrics with profiling and tracing. CPU saturation and flame graphs can reveal expensive code paths, while off-CPU profiles, queue depth, disk and network latency, lock wait time, run-queue length, and context-switch rates help identify I/O, synchronization, or scheduler issues. I confirm the hypothesis with a focused experiment before changing production architecture.
I would define user-centered latency percentiles, typically p50, p95, and p99, alongside availability, error rate, saturation, throughput, and cost per successful request. The SLO should be segmented by important request classes and include clear error-budget and alerting thresholds. Supporting service-level metrics should make it possible to attribute violations to a specific dependency or resource constraint.
A common example is decoupling synchronous work from the request path through bounded queues and asynchronous workers, while applying backpressure and admission control. I would model the workload, identify the limiting resource, benchmark the change under representative load, and verify that tail latency, reliability, and operational complexity improve rather than merely shifting the bottleneck.
I would quantify the customer, reliability, and cost impact with shared metrics, present the root-cause evidence and trade-offs, and propose a staged plan with clear owners and success criteria. Small, reversible experiments can build confidence quickly. I would keep stakeholders informed through concise decision records and ensure the final solution has measurable, durable operational outcomes.
About the Team
We bring OpenAI’s technology to the world through products like ChatGPT and the OpenAI API.
We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.
About the Role
OpenAI is looking for an experienced Performance Engineer to help us scale the performance, reliability, and efficiency of our systems. In this role, you’ll apply deep technical expertise to optimize infrastructure and application-level performance across mission-critical products like ChatGPT and our developer API. You’ll work cross-functionally with teams building core services, training models, and developing real-time user experiences to push our latency, throughput, and cost-efficiency to the next level.
We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack.
In this role, you will:
Analyze and optimize performance across application, middleware, runtime, and infrastructure layers—networking, storage, Python runtime, GPU utilization, and beyond.
Develop tooling and metrics that provide deep observability into system performance.
Collaborate closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements.
Influence architecture and design decisions to prioritize latency, throughput, and efficiency at scale.
Lead investigations into high-impact performance regressions or scalability issues in production.
Drive performance testing strategies and help define SLAs/SLOs around latency and throughput for critical systems.
You might thrive in this role if you:
Have 7+ years of experience in software engineering with a strong track record in performance or reliability of high-scale distributed systems.
Are deeply comfortable with performance profiling tools and tracing systems.
Have experience optimizing performance across one or more layers of the stack (e.g., database, networking, storage, application runtime, GC tuning, Python/Golang internals, GPU utilization).
Have a strong understanding of OS internals, scheduling, memory management, and IO patterns.
Have contributed to observability, benchmarking, or performance-focused infrastructure at scale.
Have demonstrated success navigating ambiguity and aligning stakeholders around performance goals.
Value simplicity, rigor, and collaboration when solving complex systems problems.
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.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
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