Software Engineer, Delivery / CD

DevOps Engineer · Senior · Full Time

San FranciscoUSD 210k – 490k4mo ago
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Role

What you'll do.

OpenAI is seeking a Software Engineer for their Delivery/CD team to build and operate continuous deployment systems that safely ship infrastructure and product code to production. This role focuses on creating deployment platforms, release pipelines, and rollout safety mechanisms to enable rapid, low-risk deployments across dozens of Kubernetes clusters and global regions.

Responsibilities

  • Continuous Deployment Infrastructure: Design and build CD systems that safely deploy changes across dozens of Kubernetes clusters and global regions
  • Progressive Delivery Systems: Develop canary releases, staged rollouts, and automated rollback mechanisms for safe production deployments
  • Engineering Velocity Optimization: Reduce friction in release pipelines and automate manual operational workflows to improve development speed
  • Cross-Team Collaboration: Partner with product and infrastructure teams to ensure services are deployable, observable, and resilient at scale
  • Deployment Methodology Evolution: Implement and advance GitOps, infrastructure-as-code, and progressive delivery patterns across the organization
  • Automated Health Monitoring: Build systems that evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger rollbacks
  • AI-Assisted Deployment Workflows: Develop systems supporting agent-assisted or autonomous deployment processes using modern AI tooling
  • Platform Reliability: Maintain high availability and performance of deployment infrastructure serving hundreds of engineers
  • Security Integration: Implement security scanning, compliance checks, and vulnerability assessments in deployment pipelines
  • Documentation and Training: Create comprehensive documentation and training materials for deployment platform adoption across engineering teams

Qualifications

What we look for.

Technical

  • Kubernetes Expertise

    5+ years experience with Kubernetes-based deployment systems at enterprise scale

  • Continuous Deployment Platforms

    Proven experience building or operating CD platforms serving multiple development teams

  • GitOps Proficiency

    Deep familiarity with GitOps tooling such as ArgoCD, Flux, or similar systems

  • Infrastructure as Code

    Expert-level experience with Terraform, Ansible, or similar IaC tools for cloud infrastructure management

  • Programming Languages

    Strong proficiency in Python, Go, or similar languages for building automation and platform tools

  • Cloud Platforms

    Extensive experience with AWS, GCP, or Azure for large-scale infrastructure deployment

  • Monitoring and Observability

    Experience implementing comprehensive monitoring, logging, and alerting systems for production deployments

  • Container Technologies

    Deep understanding of Docker, container orchestration, and cloud-native architecture patterns

Education

  • Degree Requirement

    Bachelor's degree in Computer Science, Engineering, or equivalent practical experience preferred

Experience

  • Platform Engineering Experience

    5-8 years in platform engineering, DevOps, or site reliability engineering roles

  • Large-Scale Systems

    Experience operating deployment systems serving 100+ engineers and thousands of deployments daily

  • Production Operations

    Strong background in production incident response, rollback procedures, and operational safety

  • Cross-Functional Leadership

    Experience working with diverse engineering teams to improve deployment practices and developer productivity

Skills

Required

  • Kubernetes

    Expert-level experience with Kubernetes cluster management, networking, and large-scale deployments

  • Python

    Advanced Python programming skills for building automation tools and platform services

  • GitOps

    Deep understanding of GitOps principles and hands-on experience with ArgoCD or Flux

  • Infrastructure as Code

    Proficiency with Terraform for managing cloud infrastructure and Kubernetes resources

  • CI/CD Pipelines

    Experience designing and implementing complex continuous integration and deployment pipelines

  • Monitoring and Alerting

    Skills in implementing comprehensive observability using Prometheus, Grafana, and similar tools

  • Container Orchestration

    Advanced knowledge of Docker, container lifecycle management, and orchestration patterns

  • Cloud Platforms

    Hands-on experience with AWS, GCP, or Azure for production-grade infrastructure

Preferred

  • Go Programming

    Nice to have

    Experience with Go for building high-performance infrastructure tools and Kubernetes operators

  • Service Mesh

    Nice to have

    Knowledge of Istio, Linkerd, or similar service mesh technologies for advanced traffic management

  • Helm Charts

    Nice to have

    Experience creating and maintaining Helm charts for complex application deployments

  • Machine Learning Operations

    Nice to have

    Understanding of MLOps practices and deploying machine learning models at scale

  • Security Tooling

    Nice to have

    Experience with security scanning tools, vulnerability management, and compliance automation

  • Incident Response

    Nice to have

    Background in production incident management, post-mortem processes, and reliability engineering

  • AI/ML Infrastructure

    Nice to have

    Interest or experience in AI model deployment, GPU cluster management, and ML infrastructure

  • Open Source Contributions

    Nice to have

    Active contributions to CNCF projects, Kubernetes ecosystem, or other relevant open source projects

Tech stack

Languages

PythonGoYAML

Frameworks

FastAPI

Databases

PostgreSQLRedis

Tools

KubernetesTerraformArgoCDBuildkiteFluxHelmPrometheusGrafanaIstio

Other

DockerGitOpsAWS/GCP/AzureOpenTelemetry

Compensation

Pay and benefits.

Base·USD 210,000 – 490,000

Equity·Stock options

Benefits

  • Equity Compensation

    Significant equity package in one of the world's leading AI companies with strong growth potential

  • Health Insurance

    Comprehensive medical, dental, and vision insurance coverage for employees and families

  • Mental Health Support

    Access to mental health resources, counseling services, and wellness programs

  • Professional Development

    Conference attendance, training budget, and opportunities to work with cutting-edge AI technologies

  • Flexible Work Arrangements

    Hybrid work options with modern office facilities in San Francisco

  • Retirement Benefits

    401(k) plan with company matching and comprehensive retirement planning resources

  • Parental Leave

    Generous parental leave policies supporting new parents with extended time off

  • Technology Stipend

    Equipment and technology allowances for optimal home office setup

  • Learning Budget

    Annual budget for books, courses, certifications, and skill development in AI and engineering

  • Commuter Benefits

    Transportation subsidies and parking allowances for San Francisco office

Process

Interview steps.

  1. 01

    Initial Screening

    30-minute phone call with recruiter covering background, motivation, and basic technical fit for the role

  2. 02

    Technical Phone Screen

    45-minute technical interview focusing on Kubernetes, CI/CD concepts, and system design fundamentals

  3. 03

    System Design Interview

    60-minute deep-dive into designing a large-scale continuous deployment system with focus on safety and scalability

  4. 04

    Technical Deep Dive

    90-minute hands-on session covering GitOps implementation, infrastructure as code, and deployment pipeline design

  5. 05

    Behavioral and Culture Fit

    45-minute interview focusing on collaboration, problem-solving approach, and alignment with OpenAI's mission

  6. 06

    Final Round Panel

    Series of conversations with team members and leadership covering technical expertise and team integration

  7. 07

    Reference Checks

    Verification of previous work experience and technical contributions with former colleagues and managers

Full posting

Original listing.

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.

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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.

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