Software Engineer, Engineering Acceleration | Consumer Devices

About the Team At OpenAI | Consumer Devices, you won’t just build products—you’ll help shape the future of how humanity interacts with intelligence. We’re looking for exceptional people who thrive on solving hard problems, move with urgency, and want their work to matter at global scale. Here, you’ll collaborate with some of the most talented minds in research, engineering, and operations to create products that millions (perhaps billions) will come to enjoy and rely on. If you’re motivated by impact, curiosity, and the chance to define what comes next, we’d like to hear from you. About the Role The Engineering Acceleration-focused engineer on the Consumer Device Infrastructure team builds the CI/CD systems, developer workflows, and internal platform capabilities that help engineers develop, test, ship, and debug software across device and cloud surfaces. This is a highly hands-on senior engineering role focused on CI/CD, software build and deployment pipelines, and developer productivity. You will design and build the technical foundations that improve engineering velocity, reduce toil, and increase software quality. You will also make pragmatic architecture and platform decisions based on the organization’s stage, scaling needs, and security requirements. We’re looking for an engineer with deep experience in developer productivity and CI/CD who enjoys building robust internal platforms, improving day-to-day engineering workflows, and creating secure, reliable systems that other engineers depend on. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and operate CI/CD systems and software delivery pipelines for software that runs both on device and in the cloud. Lead the design and architecture of internal platform capabilities across build, test, deployment, workflow automation, and developer tooling. Make hands-on technical decisions about platform design, abstraction boundaries, and system tradeoffs based on the team’s current stage, scale, and operational needs. Improve developer productivity by shortening feedback loops across build, test, debugging, environment setup, and release-adjacent workflows. Build self-serve paved-road workflows that reduce manual effort and make common engineering tasks fast, reliable, and easy to adopt. Use AI-native tooling and automation to improve engineering workflows, failure triage, and developer output quality. Build secure-by-default platform capabilities, including access controls, secrets and credential handling, artifact permissions, auditability, and policy enforcement in software delivery workflows. Partner closely with product, systems, release, quality, and infrastructure teams to understand pain points and turn them into durable platform improvements. Define and track metrics for platform health and engineering effectiveness, including build times, queue times, failure rates, flaky failures, and deployment lead time. Guide engineering teams on pragmatic observability, reliability, and scalability choices for the systems they build. Participate in the on-call rotation for the systems owned by the team. You might thrive in this role if you: Have 7+ years of software engineering experience, including 5+ years building developer productivity, CI/CD, internal platform, or engineering systems. Have deep experience designing and operating robust CI/CD pipelines, build systems, and software delivery infrastructure for complex products. Have a strong track record of personally building platform features and workflow improvements that materially increased engineering velocity, reliability, or developer experience. Have experience making architectural decisions for internal platforms, including when to standardize, when to abstract, and when to keep systems simple. Have experience adapting technical decisions to the maturity and scaling stage of an organization, balancing speed, reliability, maintainability, and adoption. Have working knowledge of secure software delivery practices such as least-privilege access, secrets management, policy enforcement, auditability, or software supply chain hardening. Have strong empathy for the tools, workflows, and frustrations that create toil or slow engineering teams down. Are comfortable operating in ambiguous, fast-changing environments and bringing structure where needed. Communicate clearly and work effectively across teams with different priorities, constraints, and technical needs. Technical Context At the heart of our infrastructure is a large-scale deployment of CPU/GPU nodes running in Kubernetes clusters across regions. We build secure systems that support software running on device and in the cloud. Some core technologies we work with include Terraform, Buildkite, Bazel, Postgres, Cosmos DB, Kafka, and more. About OpenAI OpenAI is an AI research and deployment company dedicated to