Network Operations Engineer, AI Networking

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.