We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale.

Design, build, and operate networking systems that support large-scale AI training and inference infrastructure

Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems

Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure

Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation

Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-performance GPU interconnects

Define and operationalize networking protocols, readiness criteria, and continuous validation systems

Partner closely with compute, storage, hardware, and infrastructure teams to ensure networking scales predictably with fleet growth

Contribute to architecture decisions around topology design, capacity planning, failure domains, and network reliability

Diagnose complex distributed systems and networking issues across large heterogeneous compute environments