EDA Cloud & Developer Infrastructure Engineer

Job description

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, our custom silicon program, the team works across silicon architecture, RTL design, verification, physical design, systems software, and infrastructure to deliver highly performant, efficient, and scalable hardware solutions. The Silicon & Systems team brings together hardware and software engineers to co-design and build the next generation of AI infrastructure. We operate at the intersection of silicon, systems, and software, tackling complex technical challenges across the full hardware development lifecycle, from early architecture and design through validation, deployment, and production. About the Role We’re looking for an Infrastructure Software Engineer to build and scale the infrastructure and developer workflows that power OpenAI’s custom silicon development. You’ll work closely with engineering teams across design verification, physical design, emulation, formal verification, and systems software to develop reliable, automated, and efficient workflows that accelerate hardware development. In this role, you'll own and improve the cloud infrastructure, high-performance computing (HPC) environments, CI/CD pipelines, regression systems, and data platforms that support our silicon engineering teams. You'll translate complex hardware development requirements into scalable infrastructure solutions, reducing manual overhead, improving reliability, and enabling engineers to iterate faster. This is a highly collaborative, hands-on role with opportunities to drive improvements across the entire hardware development lifecycle. We're looking for engineers who bring deep expertise in one or more infrastructure domains, strong software engineering fundamentals, and an interest in expanding their impact across the broader platform. In this role, you will: Build developer tools and workflows: Partner with hardware engineering teams to understand their development processes, identify bottlenecks, and build tooling, services, and APIs that automate workflows and accelerate engineering productivity. Develop and scale regression infrastructure: Design, implement, and operate large-scale regression systems spanning job scheduling, execution, results collection, triage, and reporting, wit…