# Network Operations Engineer, AI Networking

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** DevOps / SRE
**Salary:** $157k – $221k/yr
**Experience:** 5+ years
**Skills:** Cisco Nx-Os, Arista Eos, Nvidia Spectrum, Cumulus Linux, Juniper Junos, BGP, Ospf, Ecmp, Mlag, Lacp, Vrfs, Vlans, Roce V2, Rdma
**Posted:** 2026-07-07

> Operate and maintain large-scale Ethernet fabrics for OpenAI's AI GPU clusters and infrastructure. Troubleshoot incidents, execute changes, perform RCAs, build observability, and automate operations across data centers while partnering with engineering and vendor teams.

## Job Description

## Key Responsibilities
- Own the operational health, availability, and reliability of production AI network infrastructure across 1P and 3P data centers.
- Monitor, troubleshoot, and resolve network incidents while meeting SLOs, reducing MTTD, and minimizing MTTR.
- Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks.
- Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact.
- Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance.
- Support new AI cluster deployments, data center expansions, and infrastructure migrations in partnership with deployment and engineering teams.
- Partner with CSPs, colocation providers, Smart Hands teams, and hardware vendors to maintain production infrastructure.
- Perform root-cause analysis (RCA) for production incidents and drive permanent corrective actions.
- Build and maintain monitoring, telemetry, dashboards, and alerting to improve network observability.
- Develop and improve operational runbooks, playbooks, troubleshooting documentation, and SOPs.
- Automate repetitive operational tasks using Python and infrastructure automation frameworks to reduce toil.
- Continuously identify opportunities to improve service reliability, scalability, operational maturity, and engineering efficiency.

## Qualifications
- Bachelor’s degree in Computer Science, Network Engineering, or a related discipline, or equivalent practical experience.
- 5+ years of experience operating large-scale data center, cloud, AI, or HPC network infrastructure.
- Experience supporting production network environments with high-availability requirements.
- Hands-on experience with one or more of the following platforms: Cisco NX-OS, Arista EOS, NVIDIA Spectrum / Cumulus Linux, or Juniper JunOS.
- Strong knowledge of Layer 2 and Layer 3 networking, BGP, OSPF, ECMP, MLAG, LACP, VRFs, and VLANs.
- Experience troubleshooting physical infrastructure, including fiber optics, transceivers, DAC/AOC cables, and high-speed Ethernet links.
- Experience performing software upgrades, hardware maintenance, and production change management.
- Excellent analytical and troubleshooting skills, with the ability to communicate technical risk clearly across teams.

## Preferred Skills
- Experience operating AI or High-Performance Computing (HPC) network environments.
- Experience with NVIDIA AI networking technologies and GPU infrastructure.
- Experience supporting RoCE v2 or RDMA-based Ethernet fabrics, with a strong understanding of PFC, ECN, DCQCN, QoS, and lossless Ethernet networking.
- Experience supporting 100G, 200G, 400G, and 800G Ethernet networks.
- Experience with GPU platforms including NVIDIA HGX, DGX, GB200, or equivalent AI infrastructure.
- Experience supporting distributed storage environments such as VAST, DDN, or similar technologies.
- Experience working with cloud service providers such as AWS, Azure, or Google Cloud, and with third-party colocation providers.
- Experience with network monitoring and telemetry technologies, including Prometheus, Grafana, gNMI, streaming telemetry, SNMP, or similar tools.
- Experience developing automation using Python, Git, REST APIs, Terraform, or similar automation frameworks.

## Work Environment and On-Call
- Participate in a 24x7 on-call rotation supporting mission-critical AI infrastructure.
- Support time-sensitive production incidents, maintenance windows, capacity expansions, and network changes.
- This role requires up to 30% travel to data center locations for new turnups and acceptance activities, as needed.

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