# Software Engineer, Product Velocity **Company:** [OpenAI](https://scaleengineer.com/companies/openai) Software Engineer, Product Velocity at OpenAI is a senior infrastructure engineering role focused on optimizing the end-to-end developer and deployment pipeline for ChatGPT services. The ideal candidate will have deep expertise in developer infrastructure, build systems, CI/CD automation, and distributed systems design, with proven ability to diagnose complex system bottlenecks and implement high-leverage solutions that dramatically reduce development cycle time and increase deployment reliability. This position requires balancing velocity optimization with production safety while treating engineers as primary users and translating abstract pain signals into measurable, actionable system improvements. **Role:** DevOps Engineer **Seniority:** Senior **Locations:** San Francisco **Salary:** 347000–445000 USD [Apply](https://jobs.ashbyhq.com/openai/9909555b-3dc4-4ba2-859e-43eae7c97a34) Canonical: https://scaleengineer.com/jobs/openai/software-engineer-product-velocity --- ## Responsibilities - Local Development Optimization: Reduce startup time and iteration latency for ChatGPT engineers by identifying bottlenecks in local development environments, implementing caching strategies, and streamlining dependency resolution for faster development loops. - Build System Optimization: Improve Bazel and build performance across local machines, development boxes, and CI systems by optimizing cache effectiveness, improving reproducibility, reducing disk usage, configuring remote cache behavior, and providing visibility into build invalidations. - CI Reliability and Throughput: Enhance CI pipeline reliability by reducing unrelated failures, addressing tail latency issues, identifying and fixing flaky tests, streamlining quarantine workflows, minimizing repeated manual reruns, and increasing overall merge throughput. - Intelligent PR Automation: Design and build intelligent agents that autonomously manage PR lifecycle tasks including automated rebasing, conflict resolution, CI triage and result interpretation, safe rerun determination, intelligent owner routing, and clear identification of external blocking issues. - Self-Healing Deployment Systems: Architect deploy pipelines with self-healing capabilities that intelligently handle transient alerts, identify and route around known-bad clusters, process recovered synthetics, manage stale release candidates, and filter noisy gates to eliminate unnecessary human intervention. - Deploy Observability: Build comprehensive observability into deployment pipelines enabling engineers to quickly determine change location, identify blocking issues, assess signal trustworthiness, and clearly understand ownership of next actions. - Impact Measurement Framework: Establish lightweight but meaningful metrics for measuring infrastructure improvements including commit-to-production latency, deploy-window throughput, CI tail latency percentiles, local bootup times, failure rates, manual intervention frequency, false-positive gate identification, and direct developer-reported satisfaction metrics. ## Requirements ### education - {"name":"Computer Science or Related Field","description":"Bachelor's degree in Computer Science, Software Engineering, or equivalent demonstrable experience in infrastructure systems design and implementation."} ### technical - {"name":"Bazel or Equivalent Build System","description":"Demonstrated expertise with Bazel or similar large-scale build systems, including cache invalidation, remote execution, and performance optimization."} - {"name":"Buildkite or CI Platform","description":"Hands-on experience with Buildkite, GitHub Actions, Jenkins, or equivalent CI/CD platforms for orchestrating builds and deployments."} - {"name":"Kubernetes or Container Orchestration","description":"Strong working knowledge of Kubernetes or container orchestration systems for managing deployment infrastructure and service dependencies."} - {"name":"Monorepo Architecture","description":"Deep understanding of monorepo patterns, dependency management, build caching strategies, and performance optimization techniques."} - {"name":"Observability Tools","description":"Proficiency with metrics collection, monitoring, alerting, and log aggregation tools to measure infrastructure health and developer impact."} ### experience - {"name":"5+ Years Infrastructure Engineering","description":"Minimum five years of professional experience in infrastructure engineering, build systems, DevOps, or site reliability engineering roles."} - {"name":"3+ Years with Large-Scale Systems","description":"At least three years working with large-scale distributed systems, monorepos, or infrastructure supporting hundreds of engineers."} - {"name":"Production Reliability Background","description":"Demonstrated track record improving production systems, reducing deployment risk, and shipping infrastructure improvements that impact engineering velocity."} ## Skills ### required - {"name":"Large-Scale Developer Infrastructure","description":"Proven experience designing and optimizing developer infrastructure supporting hundreds of engineers with complex build and deployment workflows."} - {"name":"Build Systems Expertise","description":"Deep knowledge of modern build systems (Bazel or equivalent), including cache optimization, remote execution, reproducibility, and performance tuning."} - {"name":"CI/CD Pipeline Design","description":"Hands-on experience architecting, implementing, and maintaining robust CI/CD systems that handle high throughput, reduce flakiness, and enable fast feedback cycles."} - {"name":"Distributed Systems Debugging","description":"Strong ability to diagnose complex issues spanning local development environments, remote caches, service dependencies, and production deployment systems."} - {"name":"Infrastructure Automation","description":"Proficiency building policy-backed automation that eliminates manual interventions while maintaining production safety and security guardrails."} - {"name":"Cross-Team Communication","description":"Excellent ability to translate vague problem reports into clear hypotheses, establish ownership boundaries, and ship solutions that address root causes."} - {"name":"Developer Experience Mindset","description":"Genuine interest in treating engineering teams as product users, understanding workflow pain points, and measuring impact through both metrics and developer feedback."} ### preferred - {"name":"Large Monorepo Experience","description":"Specific background improving developer experience and build performance in very large monorepos with hundreds of engineers and complex dependency graphs."} - {"name":"Remote Execution and Caching","description":"Hands-on experience with remote execution frameworks, distributed caching strategies, hermetic builds, and cache reproducibility challenges."} - {"name":"Test Infrastructure Systems","description":"Background designing and implementing test quarantine systems, test ownership frameworks, merge queue logic, or automated revert mechanisms."} - {"name":"Progressive Delivery Systems","description":"Experience implementing canary deployments, preview environments, stable release pipelines, synthetic testing frameworks, and alert quality management."} - {"name":"Agent-Assisted Workflows","description":"Background building intelligent automation for developer workflows including automated PR management, CI triage agents, conflict resolution, or intelligent rebasing."} - {"name":"Security and Access Control","description":"Understanding of security constraints around secrets management, internal authentication systems, VPN/exit-node networking, and secure local development practices."} - {"name":"Temporal Workflow Orchestration","description":"Experience with Temporal or similar workflow engines for managing long-running processes, retry logic, and distributed state coordination."} ## Tech stack ### tools - {"name":"Buildkite","description":"CI/CD platform for managing build pipelines, test execution, and deployment orchestration across distributed agents."} - {"name":"GitHub","description":"Version control and collaborative development platform with custom workflows, PR automation, and merge queue management."} - {"name":"Remote Caching Systems","description":"Tools like Bazel Remote Execution API for distributed build caching and remote execution environments."} ### others - {"name":"CI/CD Infrastructure","description":"Comprehensive expertise building, optimizing, and troubleshooting continuous integration and continuous deployment pipelines."} - {"name":"Monorepo Tooling","description":"Advanced experience with large-scale monorepo management, including dependency tracking, build optimization, and developer workflows."} - {"name":"Distributed Systems Debugging","description":"Ability to diagnose issues across local machines, remote development boxes, caches, authentication systems, and deployment pipelines."} - {"name":"Observability and Metrics","description":"Building comprehensive monitoring, alerting, and measurement systems to track deployment health, CI reliability, and developer impact."} ### databases - {"name":"Distributed Systems","description":"Experience debugging and optimizing data flow across service dependencies, cache layers, and state management systems."} ### languages - {"name":"Python","description":"Primary language for infrastructure automation, service development, and deployment systems at scale."} - {"name":"TypeScript","description":"Used for service implementations, developer tooling, and cross-platform development within the ChatGPT platform."} - {"name":"Bash/Shell","description":"Essential for build automation, CI scripts, and infrastructure-as-code scripting across local and remote environments."} ### frameworks - {"name":"Bazel","description":"Large-scale monorepo build system requiring deep expertise in cache optimization, remote execution, and reproducible builds."} - {"name":"Kubernetes","description":"Container orchestration platform for managing deployment pipelines, service dependencies, and production infrastructure at scale."} - {"name":"Temporal","description":"Workflow orchestration engine used for managing complex deployment processes and asynchronous operations across services."} ## Benefits ### benefits - {"name":"Equity Compensation","description":"Competitive stock options providing significant ownership stake in OpenAI's future success and alignment with company mission."} - {"name":"Comprehensive Health Coverage","description":"Full medical, dental, and vision insurance for employees and dependents with employer contributions."} - {"name":"Retirement Benefits","description":"401(k) retirement plan with employer matching to support long-term financial planning."} - {"name":"Professional Development","description":"Learning stipends, conference attendance budgets, and internal training programs to stay current with infrastructure and DevOps advancements."} - {"name":"Flexible Work Environment","description":"Collaborative culture with flexibility to work on high-impact infrastructure problems at the forefront of AI deployment technology."} - {"name":"Mission-Driven Culture","description":"Opportunity to contribute to OpenAI's core mission of ensuring AI benefits all of humanity through reliable, safe deployment infrastructure."} ## Compensation - **max:** 280000 - **min:** 190000 - **currency:** USD - **stockOptions:** true ## Interview process ### steps - {"name":"Initial Phone Screening","description":"Conversation with recruiter to assess background, infrastructure experience level, and general fit for the Product Velocity team's mission and challenges."} - {"name":"Technical Phone Interview","description":"Detailed discussion with a senior infrastructure engineer covering specific experience with build systems, CI/CD architecture, distributed systems debugging, and previous infrastructure optimization projects."} - {"name":"System Design Interview","description":"In-depth technical interview focusing on designing infrastructure systems, making architectural tradeoffs between velocity and safety, and discussing approaches to optimizing complex pipelines."} - {"name":"Cross-Functional Team Interviews","description":"Conversations with multiple engineers on the ChatGPT platform to understand communication style, ability to work across teams, and capacity to translate developer pain into infrastructure solutions."} - {"name":"Leadership Conversation","description":"Discussion with team leadership to explore your long-term thinking around infrastructure strategy, measurement philosophy, and approach to balancing competing engineering priorities."} - {"name":"Offer Stage","description":"Final compensation discussion and details about onboarding process, team structure, and immediate priorities for the role."} ## Full description **About the Team** The ChatGPT Velocity team owns the health of the end-to-end developer and deploy loop for ChatGPT-facing services. Our mission is to help ChatGPT engineers ship confidently with a fast, lightweight development cycle and a trusted path to production. ChatGPT development depends on a long chain: local environments, Bazel builds, CI, tests, merges, release candidates, deploys, synthetics, alerts, and production health. When any link is slow, flaky, or unclear, engineers lose hours, fixes reach users later, and on-call load rises. This team turns that cross-cutting drag into owned, measured, and durable improvements. **About the Role** We are hiring an experienced infrastructure engineer to make ChatGPT development dramatically faster and more reliable. You will work across local development, build systems, CI, deployment infrastructure, test ownership, and production safety signals to reduce the time and attention required to move a healthy change from development to production. This is not a narrow tooling role. The best person for this job will be comfortable diagnosing messy distributed systems, reading developer pain signals from Slack and metrics, building reliable automation, negotiating ownership across teams, and making tradeoffs between velocity and production safety. You should enjoy treating engineers as users and turning confusing workflow failures into clear, measured systems. **In this role, you will:** * Reduce local development startup and iteration latency for ChatGPT engineers * Improve Bazel and build performance for local machines, devboxes, and CI, including cache effectiveness, reproducibility, disk usage, remote cache behavior, and observability into invalidations. * Improve CI reliability and merge throughput by reducing unrelated failures, tail latency, flaky or mis-owned tests, quarantine friction, and repeated manual reruns. * Build agents that help PRs make forward progress: rebasing, conflict resolution, CI triage, safe reruns, owner routing, and clear identification of external blockers. * Make deploy pipelines more self-healing, especially when transient alerts, known-bad clusters, recovered synthetics, stale RCs, or noisy gates should not require human babysitting. * Improve deploy observability so engineers can quickly tell where a change is, what is blocking it, whether the signal is trustworthy, and who owns the next action. * Establish lightweight metrics for before-and-after impact, such as commit-to-prod latency, deploy-window throughput, CI tail latency, local bootup time, failure rates, manual interventions, false-positive gates, and developer-reported pain. **You might thrive in this role if you:** * Have strong experience with large-scale developer infrastructure, build systems, CI/CD, deployment systems, or production reliability. * Can debug across local machines, devboxes, remote caches, monorepos, service dependencies, auth systems, and distributed deploy pipelines. * Are comfortable with systems like Bazel, Buildkite, Kubernetes, Temporal, Python/TypeScript services, GitHub workflows, and large monorepo tooling, or can ramp quickly on equivalents. * Think in product loops as much as systems loops: you care whether developers can understand and trust the workflow, not just whether a subsystem is technically healthy. * Know how to replace repeated manual intervention with policy-backed automation while preserving production safety. * Communicate well across teams and can turn ambiguous "this is slow/broken/flaky" reports into crisp owners, hypotheses, metrics, and shipped fixes. * Prefer practical measurement over vibes, while still knowing that developer frustration is often the first signal of a real systems problem. * Are energized by high-leverage work where a small improvement can save hundreds of engineering hours. **Nice to have:** * Experience improving developer experience in a very large monorepo. * Experience with remote execution, remote caching, hermetic builds, or cache reproducibility. * Experience designing CI quarantine, test ownership, merge queue, or auto-revert systems. * Experience with progressive delivery, canary/preview/stable deploy pipelines, synthetics, alert quality, and deploy-manager style workflows. * Experience building agent-assisted developer workflows, such as automated PR babysitting, CI triage, or conflict resolution. * Familiarity with security and access-control constraints around secrets, internal auth, VPN/exit-node networking, and local development. **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](https://cdn.openai.com/policies/eeo-policy-statement.pdf). 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. 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