AI Safety Tools & Infrastructure Engineer

OpenAI, Inc.; United States; Remote; USD 140,000 - 230,000; Full time

Job summary

OpenAI, Inc. is seeking a Software Engineer to build tools and infrastructure that support safety-focused research and evaluation.

You will partner with researchers and engineers to translate evolving questions into practical software—from prototypes to dependable systems. Projects include backend services, evaluation infrastructure, data pipelines, and internal applications for running tests, inspecting results, and reviewing findings.

Qualifications

• Strong software engineering fundamentals.
• Proficient in a general-purpose programming language.
• Experience building, shipping, and maintaining production software.
• Ability to take open-ended problems and deliver practical solutions.
• Balance rapid iteration with maintainable design and operational reliability.
• Clear communication across technical disciplines.
• Interest in AI safety, security, and evaluating model behavior.

Responsibilities

• Design, build, and maintain software that supports cybersecurity research, frontier-risk evaluations, and red teaming.
• Develop tools and workflows to run evaluations, inspect results, and investigate failures.
• Build services, APIs, data pipelines, and interfaces to help researchers work efficiently.
• Turn experimental workflows into reusable, well-tested, and documented systems.
• Own projects from problem understanding to deployment and operation.
• Improve reliability, performance, observability, security, and usability as needs evolve.
• Collaborate with researchers, security specialists, and engineers to identify useful problems and make decisions.

Skills

Software fundamentals

General-purpose programming

Backend development

Full-stack

Infrastructure

Data systems

Problem solving

Cross-disciplinary collaboration

Job description

OpenAI, Inc. is seeking a Software Engineer to build tools and infrastructure that support safety-focused research and evaluation.

You will partner with researchers and engineers to translate evolving questions into practical software—from prototypes to dependable systems. Projects include backend services, evaluation infrastructure, data pipelines, and internal applications for running tests, inspecting results, and reviewing findings.