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, with a focus on performance, reliability, and reproducibility.

Own CI/CD infrastructure: Build and maintain automated pipelines for infrastructure, developer tooling, and cluster configurations, enabling safe deployments, testing, and continuous improvement.

Scale cloud and HPC environments: Design, provision, and operate cloud infrastructure and high-performance compute clusters, optimizing scheduling, capacity, reliability, and cost efficiency to support demanding silicon development workloads.

Build data infrastructure and observability: Develop data pipelines, databases, and monitoring systems that provide visibility into regression results, infrastructure health, resource utilization, and engineering efficiency.

Drive platform reliability and operational excellence: Troubleshoot complex infrastructure issues, improve monitoring and alerting, automate recovery processes, and build systems that are resilient, maintainable, and scalable.

Collaborate across hardware and software teams: Work directly with engineers across RTL, verification, physical design, emulation, and software to continuously improve the infrastructure supporting OpenAI's silicon development.

You might thrive in this role if you

Have strong software engineering fundamentals, with proficiency in Python or a similar programming language and experience building reliable automation, tools, or infrastructure services.

Bring deep technical expertise in at least one area of infrastructure engineering, such as Linux/HPC environments, cloud infrastructure, CI/CD systems, storage, networking, or EDA development workflows.

Have experience designing, deploying, and operating cloud infrastructure, preferably Azure, with familiarity in infrastructure-as-code tools such as Terraform or Bicep.