Senior Automation Engineer, Compute

The role

You will be responsible for deployment and testing automation of large-scale, multi-node GPU clusters. You will develop CI/CD infrastructure for a fleet of virtualized GPU and CPU hosts across the AI Cloud.

What you will do

• Develop applications and systems for deployment and integration testing on bare-metal, on-premise systems.
• Build CI/CD platforms to enable developers to test, iterate, and deploy low-level systems and applications.
• Design and execute large-scale validation tests across multi-node virtualized clusters.
• Maintain and scale bare-metal Linux configurations using tools such as Gitlab, Ansible, and osquery.
• Create control applications to coordinate canary deployments, Blue/Green testing, and automatic rollback.
• Develop and maintain automation frameworks in Python or Go to provision, configure, and stress-test environments.
• Create automated test suites leveraging tools like fio, stress-ng, and iperf.

Required qualifications

• 5+ YOE demonstrated ability to competently and independently perform responsibilities
• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field
• Experience building and deploying automated integration testing, ranging from low-level Linux Systems up to Distributed Control Planes
• Proven track record of designing and deploying microservice applications end to end in a distributed Cloud Environment
• Strong understanding of how cloud resources (Compute, Network, Storage) are abstracted and managed in an IaaS environment
• Working knowledge of the modern infrastructure stack, including Kubernetes, Docker, Terraform, and Postgres
• Intimate knowledge of CI/CD pipelines and Gitlab Tooling
• Previous experience with at least 1-2 configuration management systems, including Ansible, Puppet, Chef, or SaltStack
• Knowledge of Linux kernel internals, specifically PCIe topology, VFIO, and memory management (HugePages, IOMMU)

Nice to have

• Familiarity with NVIDIA (CUDA/NCCL) and/or AMD (ROCm/RCCL) stacks in a multi-node context
• Understanding of RDMA, RoCE, and InfiniBand protocols and their implementation in virtualized systems
• Experience with MNNVL (Multi-Node NVLink) or specialized AI fabric architectures
• Familiarity with hardware-level debugging tools and performance profilers (e.g., NVIDIA Nsight, AMD Omniperf)
• Knowledge of containerized orchestration for GPUs (e.g., Kubernetes with specialized device plugins)

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.