Sr Ethernet AI Network Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Sr Ethernet AI Network Engineer based in the United States.

As a Senior Ethernet AI Network Engineer, you will help design, deploy, and maintain high-performance Ethernet fabrics that power advanced AI and high-performance computing (HPC) environments. You will ensure network infrastructure can support demanding distributed training workloads, high-bandwidth data transfers, and large-scale GPU cluster communications. Working across the full network stack, you will troubleshoot complex connectivity and performance issues, optimize traffic behavior, and validate the reliability of critical data center infrastructure. You will collaborate closely with Linux, storage, and cluster deployment teams to identify root causes and maintain seamless operations. This remote opportunity is suited to an experienced networking professional who enjoys solving complex infrastructure challenges and building scalable operational standards for next-generation AI environments.

• Deploy, validate, and support Ethernet network fabrics for AI and high-performance computing (HPC) cluster environments.

• Troubleshoot network issues across Layers 1 through 4, including optics, transceivers, cabling, link initialization, VLANs, MLAG, ECMP, BGP, underlay and overlay reachability, congestion, and packet loss.

• Validate network readiness for distributed AI training and high-volume east-west traffic patterns.

• Diagnose and resolve network performance issues involving buffer pressure, microbursts, Priority Flow Control (PFC), Quality of Service (QoS) policies, MTU mismatches, routing instability, and oversubscription.

• Work closely with Linux, storage, and cluster deployment teams to isolate host-related issues from network infrastructure problems.

• Review and execute network change plans covering switch provisioning, firmware upgrades, topology expansions, and scheduled maintenance activities.

• Collect and analyze packet-level information, network counters, and telemetry data to support troubleshooting and root-cause investigations.

• Establish and maintain operational standards for cable mapping, port configuration consistency, and network fabric health validation.

• Document network incidents, topology changes, troubleshooting findings, and remediation plans to support operational reliability and continuous improvement.

Requirements:

• At least 7 years of experience in large-scale data center networking, including high-bandwidth Ethernet fabrics.

• Strong expertise in spine-leaf network architecture, routing, switching, and production network troubleshooting.

• Hands-on experience with BGP, EVPN/VXLAN, MLAG, ECMP, QoS, PFC, and RoCE-related networking considerations.

• Ability to interpret network telemetry and diagnose complex connectivity, congestion, and performance issues.

• Experience validating optical transceivers, breakout configurations, cabling infrastructure, and port-level configuration consistency.

• Demonstrated ability to troubleshoot distributed application performance issues caused by network behavior.

• Practical experience using switch command-line interfaces, network automation tools, and packet and counter analysis workflows.

• Strong documentation skills, including maintaining network topology records, incident timelines, technical findings, and remediation plans.

• Excellent analytical and problem-solving abilities, with the capacity to investigate complex issues across multiple network layers.

• Strong communication and collaboration skills, particularly when working with infrastructure, Linux, storage, and cluster engineering teams.

• Direct experience with AI networking fabrics supporting large-scale GPU collective traffic is preferred.

• Familiarity with SONiC, Cumulus Linux, or other network operating systems used in AI data center environments is an advantage.

• Experience with streaming telemetry, Prometheus, Grafana, and network Site Reliability Engineering (SRE) operating models is preferred.

Benefits:

• Remote working arrangement.

• Opportunity to contribute to advanced AI and high-performance computing infrastructure.

• Exposure to large-scale, high-bandwidth Ethernet environments and modern data center technologies.

• Opportunities to deepen expertise in AI networking, GPU cluster infrastructure, and network automation.

• Collaborative environment that encourages ownership, continuous learning, and professional growth.

• Opportunity to take on meaningful technical challenges and contribute to the development of next-generation network infrastructure.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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