Software Engineer, Core Network Engineering

About the Team

The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure.

About the Role

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.

In this role, you will:

• 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

You might thrive in this role if you:

• Have experience building or operating large-scale networking or distributed systems infrastructure
• Are comfortable working close to the hardware/software boundary
• Have experience with Linux networking, kernel systems, NICs, RDMA, or performance-sensitive infrastructure software
• Have worked with high-performance networking technologies such as InfiniBand, RoCE, DPDK, or large-scale Ethernet fabrics
• Have experience with datacenter networking, WAN systems, or host networking stacks
• Enjoy debugging complex systems and performance bottlenecks across multiple layers of the stack
• Are comfortable writing production software in languages such as C++, Python, or Go
• Have strong systems fundamentals across networking, operating systems, distributed systems, or infrastructure engineering
• Are motivated by building infrastructure that directly accelerates frontier AI research and deployment