OpenAI· IT· San Francisco, New York City, Seattle, and Remote - US
Software Engineer, Identity Infrastructure Engineering
Comp$184K – $346.5K
Classified Tasks (18)
Automate 0%Augment 67%Human-Only 33%
Augment (12)
AI assists, human decides
Create foundational security tools and infrastructure.
technical
Deploy foundational security tools and infrastructure.
operational
Operate foundational security tools and infrastructure.
operational
Build and maintain systems and interfaces that manage user and service identity.
technical
Ensure fine-grained access controls are consistent across cloud providers and internal services.
technical
Develop robust frameworks, APIs, and CLI tools that automate recurring security tasks such as provisioning and rotating credentials.
technical
Build new features for the IAM platform that integrate with evolving cloud services.
technical
Implement and refine access policies that protect high-value assets including model weights and customer data.
administrative
Support multi-cloud deployments to enable researchers and engineers to safely build, test, and scale AI systems.
operational
Embed secure-by-default principles into every layer of the software stack.
leadership
Provide a secure and scalable platform for permissioning and orchestration by partnering with Applied Engineering, Research, IT, and Security teams.
leadership
Ensure identity and access solutions operate seamlessly across AWS, Azure, and GCP.
technical
Human-Only (6)
Requires human judgment
Design and build identity and access management solutions that protect model weights, customer data, and critical systems across multiple cloud environments.
technical
Design architectures and tooling that protect model weights, custom data, and sensitive assets in AWS, Azure, GCP, and future cloud environments.
technical
Design tools, processes, and architectures that protect data at scale.
technical
Collaborate cross-functionally with researchers, engineers, and compliance teams to address security requirements for multi-cloud deployments, large-scale model training, and emerging AI use cases.
communication
Troubleshoot complex identity and access issues across distributed systems to minimize downtime.
operational
Reinforce a secure development culture across the organization through tooling and process design.
leadership
Job description
Software Engineer, Identity Infrastructure Engineering | OpenAI Careers ## Software Engineer, Identity Infrastructure Engineering IT - San Francisco, New York City, Seattle, and Remote - US Apply now(opens in a new window) **About the Team** Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect our model weights, customer data, and critical systems across multiple cloud environments. We partner with teams across OpenAI—Applied Engineering, Research, IT, and Security—to provide a secure and scalable platform for permissioning, orchestration, and innovative AI research. The role is preferred to be based in San Francisco, Seattle or New York City but may consider remote work. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. **About the Role** As a **Software Engineer on the Identity Infrastructure Engineering team**, you’ll be instrumental in creating, deploying, and operating foundational security tools and infrastructure. You will work with a broad range of technologies to support multi-cloud deployments, ensuring that researchers and engineers can safely build, test, and scale transformative AI systems. The role requires a balance of strong technical depth, cross-functional collaboration, and a passion for embedding secure-by-default principles into every layer of our stack. We are looking for Software Engineers interested in coming to tackle challenges in these areas: * **Identity & Access Orchestration**: Build and maintain the systems and interfaces that manage user and service identity, ensuring fine-grained access controls are consistent across cloud providers and internal services. * **Multi-Cloud Security**: Design architectures and tooling that protect model weights, custom data, and sensitive assets while operating seamlessly in AWS, Azure, GCP, or future cloud environments. * **Automation & Tooling**: Develop robust frameworks, APIs, and CLI tools that automate recurring security tasks (like provisioning or rotating credentials), freeing teams to focus on AI innovation without sacrificing security. **In this role, you will:** * Build new features for our IAM platform that seamlessly integrate with evolving cloud services, enabling teams to work efficiently while adhering to security best practices. * Drive security innovation by designing tools, processes, and architectures that protect data at scale and reinforce a secure development culture across the organization. * Collaborate cross-functionally with researchers, engineers, and compliance teams to address security requirements for multi-cloud deployments, large-scale model training, and emerging AI use cases. * Implement and refine access policies that strike the right balance between enabling rapid experimentation and protecting high-value assets, including model weights and customer data. * Troubleshoot complex identity or access issues across distributed systems, ensuring minimal downtime and a safe environment for AI research and product teams. **You might thrive in this role if you:** * A background in building secure systems—from core IAM services to orchestration layers that manage credentials, roles, or policies at scale. * Proficiency in programming languages such as Python, Go, or similar, with a track record of writing high-quality, maintainable code. * Experience with modern cloud infrastructure (AWS, Azure, GCP) and familiarity with industry-standard security protocols (OAuth, SAML, OpenID Connect) and authentication/authorization patterns. * A security-focused mindset, with knowledge of threat modeling, risk assessment, and the ability to embed security features throughout the software development lifecycle. * E