Software Engineer, Agent Infrastructure
About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a worksp
What this role actually needs.
About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a worksp Responsibilities: - Push massive compute clusters to their limits. You will be a core contributor to a novel container orchestration platform built in-house by our team to scale far beyond what’s possible with systems like Kubernetes. - Develop and maintain FastAPI and gRPC APIs that serve as the interface for our agentic infrastructure used both in training and production. - Use Terraform to stand up and evolve complex infrastructure for both research and production. - Collaborate with research teams to stand up and optimize systems for novel AI training runs and experimental applications. - Have deep experience working on large-scale machine learning infrastructure. You know how to reason about training at scale, identifying bottlenecks and engineering solutions to optimize system performance in training environments. - Know how to build new things from 0-1 quickly, and then scale them 1,000,000x. Company context: OpenAI builds frontier AI systems, research infrastructure, and applied products for developers, enterprises, and global users.
Day-to-day expectations
OpenAI lists these responsibilities for the Software Engineer, Agent Infrastructure role.
- Push massive compute clusters to their limits. You will be a core contributor to a novel container orchestration platform built in-house by our team to scale far beyond what’s possible with systems like Kubernetes.
- Develop and maintain FastAPI and gRPC APIs that serve as the interface for our agentic infrastructure used both in training and production.
- Use Terraform to stand up and evolve complex infrastructure for both research and production.
- Collaborate with research teams to stand up and optimize systems for novel AI training runs and experimental applications.
- Have deep experience working on large-scale machine learning infrastructure. You know how to reason about training at scale, identifying bottlenecks and engineering solutions to optimize system performance in training environments.
- Know how to build new things from 0-1 quickly, and then scale them 1,000,000x.
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Source: jobs.ashbyhq.com · Source ID: c1316397-25bb-4add-9e9d-0e3ea8ba929a · Confidence: 97/100 · Last checked: May 7, 2026
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