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Network Engineer (AI GPU Cluster Operations)

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Onsite

Network Engineer (AI GPU Cluster Operations)

Aquila Hash, Inc.

Network Engineer (AI GPU Cluster Operations)

Skills

NodePythonGrafanaAIAnsiblePrometheusLinuxITILTerraform

1 month ago

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Important information


Contract type:

Permanent

Location:

Buffalo, NY, USA

Work mode:

Onsite

Published on:

13 September 2026

What they need


Position Overview

The AI GPU Cluster Operations – Network Engineer is responsible for the operations, maintenance and troubleshooting of high-performance networking infrastructure supporting large-scale AI GPU computing clusters.

The role focuses on InfiniBand, RoCE and data center IP networks, while also requiring a strong understanding of GPU servers, Linux and the overall AI cluster architecture.

The engineer will monitor network and cluster health, troubleshoot connectivity and performance issues, maintain high-speed network infrastructure, support production incidents, implement approved network changes and work with internal engineering teams and OEM vendors to drive technical issues through resolution.

Key Responsibilities

  • Operate and maintain high-performance GPU cluster networks, including InfiniBand and RoCE, as well as standard data center IP networks.

  • Manage and troubleshoot NVIDIA/Mellanox InfiniBand switches, high-speed Ethernet switches, NICs/HCAs, optical transceivers, cables and related network infrastructure.

  • Monitor network health and identify link degradation, link flapping, congestion, packet loss, bandwidth or latency issues.

  • Perform InfiniBand health checks and diagnostics using tools such as ibstat, ibdiagnet and other NVIDIA/Mellanox diagnostic utilities.

  • Support InfiniBand Subnet Management, partition configuration, routing, link-health monitoring and performance-counter analysis.

  • Troubleshoot RoCE environments, including connectivity, congestion and lossless Ethernet-related issues.

  • Support data center IP network operations, including BGP, OSPF, VLAN, MLAG and TCP/IP.

  • Troubleshoot GPU node connectivity and determine whether infrastructure issues originate from the server, NIC/HCA, optics, cabling, switch or network fabric.

  • Work with GPU Cluster Operations Engineers to troubleshoot GPU-to-GPU and node-to-node communication issues, including network-related NCCL failures and performance degradation.

  • Monitor network and infrastructure health using Prometheus, SNMP, Grafana and related monitoring platforms.

  • Develop and maintain network monitoring, alerting and diagnostic capabilities.

  • Perform approved network configuration changes, maintenance and upgrades according to established change-management procedures and Standard Operating Procedures (SOPs).

  • Support network capacity planning and expansion of GPU cluster infrastructure.

  • Use Python, Shell, Ansible and/or Terraform to automate network configuration, health checks, monitoring and repetitive operational tasks.

  • Participate in infrastructure incident response, troubleshooting, post-incident reviews and Root Cause Analysis (RCA).

  • Maintain network diagrams, configuration documentation, SOPs, troubleshooting guides and operational records.

  • Coordinate with NVIDIA/Mellanox, server OEMs, network vendors and other technical support teams to resolve hardware and network issues.

  • Support hardware replacement and RMA activities for switches, NICs/HCAs, optical transceivers and other network components.

Qualifications

  • Degree or relevant educational background in Computer Science, Information Technology, Networking, Telecommunications, Engineering or a related field.

  • 3+ years of hands-on network operations, data center networking or infrastructure experience.

  • Hands-on experience operating InfiniBand and/or RoCE networks in GPU, AI, HPC or large-scale data center environments.

  • Experience with NVIDIA/Mellanox InfiniBand or high-speed Ethernet networking equipment is strongly preferred.

  • Understanding of InfiniBand architecture, including Subnet Management, partitions, routing, link states and performance counters.

  • Strong understanding of TCP/IP and data center networking.

  • Working knowledge of BGP, OSPF, VLAN and MLAG.

  • Ability to troubleshoot high-speed network connectivity, link degradation, congestion, packet loss and performance issues.

  • Hands-on ability to troubleshoot switches, NICs/HCAs, optical transceivers, cables and switch ports.

  • Familiarity with InfiniBand diagnostic tools such as ibstat and ibdiagnet.

  • Familiarity with Linux and command-line troubleshooting.

  • Experience with monitoring platforms and protocols such as Prometheus, SNMP and Grafana.

  • Ability to write basic Python and/or Shell scripts for troubleshooting and automation.

  • Experience with Ansible and/or Terraform is preferred.

  • Good understanding of GPU cluster architecture and the relationship between GPU servers, NICs/HCAs and high-performance network fabrics.

  • Strong troubleshooting, documentation and Root Cause Analysis (RCA) capabilities.

  • Strong sense of ownership and ability to work effectively during production incidents.

Preferred Qualifications

  • Experience supporting large-scale 1,000+ GPU clusters; experience with 10,000+ GPU environments is a strong plus.

  • Experience supporting NVIDIA H100/H200/B200 or AMD MI300X/MI355X GPU infrastructure.

  • Experience operating 100G/200G/400G or higher-speed InfiniBand or Ethernet networks.

  • Experience troubleshooting NCCL and GPU communication issues from the network/fabric perspective.

  • Experience with NVIDIA/Mellanox network management and diagnostic tools.

  • Experience with network automation using Python, Shell, Ansible or Terraform.

  • CCNP, CCIE or other relevant networking certifications are a plus.

  • Experience working within ITIL-based incident, problem and change-management processes.

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