C
Posted 10 hours ago
Staff Network Deployment Engineer
CrusoeStaff Network Deployment Engineer, Lab
Perks & benefits
Education AllowanceHealth Insurance
Requirements
8+ years network engineering experience, Data center deployment expertise, Structured cabling knowledge, Arista, Juniper, and NVIDIA/Mellanox experience, BGP and EVPN-VXLAN proficiency, Python and Ansible proficiency
Skills
PythonAnsibleBGPAristaJuniper
About the role
Responsibilities
- Lead end-to-end deployment of network infrastructure for the Crusoe lab
- Translate high-level designs into implementation plans, cable maps, and configuration templates
- Perform rigorous burn-in and acceptance testing (SAT) for new network clusters
- Automate staging and configuration of network devices using Python, Ansible, and ZTP
- Manage lab environment including GPU systems, networking devices, and physical layer standards
- Perform diagnosis and troubleshooting of hardware faults and component-level remediation
- Support networking for GPU platforms including NVIDIA and AMD systems
- Partner with data center operations for FRU repairs and firmware/BIOS upgrades
- Maintain detailed documentation of maintenance, failures, and resolutions
- Develop and update standard operating procedures (SOPs) for troubleshooting and validation
- Participate in a rotating infrastructure on-call schedule
Requirements
- 8+ years of experience in network engineering with a focus on large-scale data center deployments
- Expert knowledge of structured cabling (SMF/MMF, MPO/MTP) and optical transceivers (400G/800G)
- Hands-on experience with Arista (EOS), Juniper (Junos), and NVIDIA/Mellanox platforms
- Solid understanding of BGP and EVPN-VXLAN in leaf-spine architectures
- Proficiency in Python and Ansible for automation
- Ability to diagnose physical layer issues using OTDRs, light meters, and packet captures
- Bachelor’s degree in a technical field or equivalent practical experience
About the Company
Crusoe is a vertically integrated AI infrastructure company that owns and operates each layer of the stack to power the world's most ambitious AI workloads through an energy-first approach.
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Crusoe · San Francisco
