Software Engineer, Agent Infrastructure
Builds and scales infrastructure for training and deploying AI agents, including novel container orchestration beyond Kubernetes, FastAPI/gRPC APIs, and Terraform-based systems. Collaborates with researchers on high-scale ML environments and production platforms for OpenAI products.
About the job
Responsibilities
- Push massive compute clusters to their limits as a core contributor to a novel in-house container orchestration platform that scales beyond Kubernetes.
- Develop and maintain FastAPI and gRPC APIs serving as the interface for agentic infrastructure in training and production.
- Use Terraform to stand up and evolve complex infrastructure for research and production.
- Collaborate with research teams to stand up and optimize systems for novel AI training runs and experimental applications.
Requirements
- Deep experience working on large-scale machine learning infrastructure, reasoning about training at scale, identifying bottlenecks, and engineering optimization solutions.
- Ability to build new things from 0-1 quickly and scale them 1,000,000x.
- Keen eye for performance and optimization in complex, globally-distributed systems.
- Experience with cloud platforms and infrastructure-as-code like Terraform.
- Driven by solving complex, ambiguous problems at the intersection of infrastructure scalability, virtualization efficiency, and agentic capabilities.
- Deep technical expertise in virtualization and containerization technologies (e.g. Kata, Firecracker, gVisor, Sysbox) and passion for optimizing runtime performance.
Skills
Kubernetes, FastAPI, gRPC, Terraform, Kata, Firecracker, Gvisor, Sysbox, Container Orchestration, Machine Learning Infrastructure
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