Crusoe
Senior Network Production Engineer, Deployment
$170K–$205K
San Francisco, CA - US +2 · On-site · Senior · Full-time · Posted Sep 23, 2026
- Location
- San Francisco, CA - US
Sunnyvale, CA - US
Bellevue, WA - US - Experience
- 5+ years.
- Education
- Bachelor's degree in a technical field or equivalent practical experience in hyperscale or ISP environments.
About the job
Deploys, configures, tests, and troubleshoots physical and logical networks for new data centers and edge sites, then hands them off to Operations.
What you'll do
- Execute network deployments from rack-and-stack through cutover, including site-specific implementation planning.
- Develop and maintain Python/Ansible automation and ZTP workflows; configure and troubleshoot network fabrics and support acceptance testing.
- Coordinate physical-layer work with vendors and data center providers, track inventory and capacity, and participate in on-call support.
What they ask for
- 5+ years of network engineering experience focused on large-scale data center deployments and infrastructure projects.
- Hands-on experience with Arista (EOS), Juniper (Junos), and NVIDIA/Mellanox platforms in leaf-spine architecture; working understanding of BGP, EVPN-VXLAN, and LLDP.
- Proficiency in Python and Ansible; experience with structured cabling, optical transceivers, and physical/link-layer diagnostics using OTDRs, light meters, and packet captures.
- Bachelor's degree in a technical field or equivalent practical experience in hyperscale or ISP environments.
Nice to have
- Experience in hyperscale, ISP, or large multi-tenant data center environments; familiarity with GPU cluster networking.
- Exposure to Prometheus, Grafana, or telemetry-based fabric health checks; vendor certifications such as CCNP, JNCIP, or Arista ACE.
Pay
up to $170,000 - $205,000 USD + Bonus (compensation; base salary or total pay not specified)
Tools
Python, Ansible, ZTP, Arista (EOS), Juniper (Junos), NVIDIA/Mellanox, BGP, EVPN-VXLAN
AI focus
Enables AI cloud infrastructure by deploying and maintaining networks for HPC and GPU-based AI infrastructure.
Model-written summary · the original posting is authoritative