Strategic Overview
Software Engineer, Delivery / CD at OpenAI is a dev opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback.
The role is listed for San Francisco with the working arrangement published with the role, giving candidates the practical context needed to assess fit before applying. Relevant signals in the listing include Applied AI, Applied AI Infrastructure.
Key information at a glance
About This Role
About the Role
The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production.
We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous.
Key Responsibilities & Objectives
- Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions.
- Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback.
- Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows.
- Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale.
Required Qualifications & Candidate Blueprint
- Have worked with Kubernetes-based deployment systems at scale
Salary & Benefits
Published compensation: $210K – $490K
- Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks.
Salary Benchmark
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Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
About the Role
The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production.
We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous.
This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration.
In This Role, You Will
Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions.
Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback.
Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows.
Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale.
Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns.
Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks.
Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling.
Technologies commonly used in this environment include:
Kubernetes for large-scale container orchestration and runtime infrastructure
Python and FastAPI for internal services
Terraform for infrastructure as code
GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems)
Buildkite for CI orchestration
You may be a strong fit if you:
Have worked with Kubernetes-based deployment systems at scale
Have experience building or operating continuous deployment platforms
Are familiar with GitOps tooling such as ArgoCD or Flux
Are excited about building AI-assisted systems and agents that intelligently shepherd software changes from commit to safe production rollout.
Care deeply about safe production rollouts and minimizing blast radius
Enjoy building internal platforms that improve developer productivity across the organization
Compensation
$230K – $490K + Offers Equity
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.
OpenAI Global Applicant Privacy Policy
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This dev opening is a useful opportunity for candidates whose experience matches Applied AI, Applied AI Infrastructure. Its strongest career signal is the scope of the work itself — particularly Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground Applied AI, Applied AI Infrastructure, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.