Senior Network Engineer

ENGAGEMENT SUMMARY

The Candidate will provide senior network engineering services for Ethernet-based AI data center fabrics

supporting GPU compute clusters, storage connectivity, and management plane services. The role requires

strong operational judgment, hands-on troubleshooting, and the ability to resolve failures across spine-leaf

architectures under production pressure.

WHAT THIS CANDIDATE WILL BE DOING

• Deploy, validate, and support Ethernet fabrics used for AI and HPC cluster environments.

• Troubleshoot L1 through L4 issues involving optics, transceivers, cabling, link bring-up, VLANs, MLAG,

ECMP, BGP, underlay/overlay reachability, congestion, and packet loss.

• Validate network readiness for distributed training and large east-west traffic patterns.

• Diagnose performance issues related to buffer pressure, microbursts, PFC behavior, QoS policy, MTU

mismatch, routing instability, and oversubscription.

• Work closely with Linux, storage, and cluster deployment teams to isolate host-versus-network fault

domains.

• Review and execute change plans for switch provisioning, firmware upgrades, topology expansion, and

maintenance events.

• Capture packet-level and counter-based evidence to drive root cause analysis.

• Build operational standards for cable mapping, port policy consistency, and fabric health validation.

WHAT WE NEE D TO SEE

• 7+ years in large-scale data center networking, including high-bandwidth Ethernet fabrics.

• Strong experience with spine-leaf design, routing, switching, and production troubleshooting.

• Hands-on skill with BGP, EVPN/VXLAN, MLAG, ECMP, QoS, PFC, RoCE considerations, and telemetry

interpretation.

• Experience validating optics, breakout configurations, cable plant integrity, and port-level consistency.

• Proven ability to troubleshoot distributed application impact caused by network behavior.

• Comfort using switch CLI, automation tooling, and packet/counter analysis workflows.

• Strong documentation habits for topology, incident timelines, and remediation plans.

PREFERRED EXPERIENCE

• Direct experience with AI fabrics carrying large-scale GPU collective traffic.

• Familiarity with SONiC, Cumulus Linux, or vendor NOS platforms used in AI data centers.

• Experience with streaming telemetry, PrometheGrafana, and network SRE operating models