Senior Network Engineer (AI)

Location: Houston, New York, San Francisco, or Seattle, United States

Company

Nscale provides a GPU cloud and high-performance infrastructure for AI startups and enterprise customers.

What you will do

• Design, deploy, and operate high-speed Ethernet front-end networks, including data center fabrics, management networks, inference traffic paths, and storage connectivity.
• Work with deployment teams on bills of materials, optics, cabling, and hardware selection.
• Contribute to data center layouts, rack elevations, and scalable reference architectures.
• Troubleshoot routing, optics, connectivity, performance, and long-haul circuit issues.
• Automate the deployment and daily operation of multi-vendor Ethernet hardware and platforms.
• Design and support WAN, data center interconnect, carrier circuits, long-haul infrastructure, and internet transit while collaborating with Architecture and Operations.

Requirements

• Experience designing, deploying, and operating high-speed Ethernet networks.
• Knowledge of VLAN, LACP, MLAG, BGP, OSPF, EVPN, and VXLAN.
• Strong knowledge of WAN and long-haul technologies, including MPLS, IPsec, GRE, SD-WAN, and carrier Ethernet.
• Understanding of data center networking topologies and front-end infrastructure best practices.
• Strong Python or Bash scripting skills for automation and tooling.
• Strong knowledge of optics, hardware, BOM design, cabling standards, reliability, and operational automation.

Nice to have

• Hands-on experience with Arista EOS or Nokia networking platforms.
• Experience with large-scale DCI, long-haul optical transport, or carrier circuit management.
• Familiarity with storage networking over Ethernet, network automation frameworks, validation tooling, or observability platforms such as streaming telemetry, Prometheus, or Grafana.
• Exposure to AI or hyperscale infrastructure environments.

Culture & Benefits

• Work in an engineering culture centered on innovation, ownership, accountability, openness, and transparency.
• Contribute to infrastructure supporting AI development, cost management, rapid innovation, and environmental responsibility.
• Collaborate across Engineering, Architecture, Operations, deployment, and support teams.