Crusoe
Staff Network Engineer, Storage
Sunnyvale, CA - US. Posted a month ago
The role
The Staff Network Engineer will architect and own a storage network end to end from spine to leaf. This role involves designing the backbone of storage infrastructure and building automation and tooling for scale.
What you will do
- Architect and operate the storage network end to end
- Trace packets through the switch pipeline and find root cause under production pressure
- Work down into the OS network stack, NIC drivers, and the software layer
- Build automation and tooling for debugging, monitoring, and operating at scale
- Partner with SDN and Network Edge teams
- Translate network reality into storage context and storage needs into network architecture
Required qualifications
- Real, battle-tested L2/L3 networking experience
- Scripting and debugging instincts to chase problems to the TCP/IP level
- Ability to pass a background check
Nice to have
- Spine-layer switch expertise
- Hands-on experience with RDMA, RoCEv2, DCQCN/PFC, or similar lossless, low-latency technologies
- A software-defined networking mindset
- Comfort reasoning about the client side of the network including OS stack behavior and NIC drivers
- Exposure to storage protocols like NFS
- A background at a storage-infrastructure company
- Deep hands-on switch experience from a hyperscale/cloud environment (AWS, Azure, GCP)
Benefits
- Competitive compensation and equity packages
- Restricted Stock Units
- Paid time off, paid holidays & leave of absence programs
- Comprehensive health, dental & vision insurance
- Employer contributions to HSA account
- Paid parental leave
- Paid life insurance, short-term and long-term disability
- Professional development & tuition reimbursement
- Mental health & wellness support
- Commuter benefits (parking & transit)
- Cell phone stipend
- 401(k) Retirement plan with company match up to 4% of salary
About the company
Crusoe is a vertically integrated AI infrastructure company that owns and operates each layer of the stack to power AI workloads. They use an energy-first approach to build AI infrastructure.