Role Overview
The Senior Staff Deployment Automation Engineer role at Crusoe is an onsite position based in San Francisco, CA, focused on managing deployment and testing automation for large-scale GPU clusters. This opportunity suits an experienced infrastructure professional looking to drive the CI/CD and deployment strategies for a rapidly scaling AI cloud platform.
Key Responsibilities
Own the deployment and integration testing automation for all bare-metal, on-premise systems across the AI cloud stack.
Build CI/CD platforms that empower developers to rapidly test, iterate, and deploy critical low-level systems and applications.
Design and execute large-scale validation tests across multi-node virtualized clusters to guarantee linear scaling and stability for GPU workloads.
Maintain and scale bare-metal Linux configurations using a combination of custom and standard tooling like GitLab, Ansible, AWX, and osquery.
Create control applications to coordinate canary deployments on live production systems, execute Blue/Green testing, and implement automatic rollbacks.
Develop and maintain automation frameworks to dynamically provision, configure, and stress-test multi-node virtualized environments.
Build automated test suites utilizing tools such as fio, stress-ng, and iperf to verify performance and multi-tenant isolation.
Requirements
Demonstrated ability to independently perform responsibilities alongside a Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field.
Experience building and deploying automated integration testing for an AI cloud environment, spanning from low-level Linux systems to distributed control planes.
Working knowledge of the modern infrastructure stack, including Kubernetes, Docker, Terraform, and Postgres.
In-depth knowledge of CI/CD pipelines and GitLab tooling for stable infrastructure releases across multiple datacenters.
Previous hands-on experience with configuration management systems like Ansible, Puppet, Chef, or SaltStack.
Advanced proficiency in Python and/or Bash for automating complex cluster-wide test scenarios.
Solid understanding of Linux kernel internals, including PCIe topology, VFIO, and memory management such as HugePages and IOMMU.
Familiarity with distributed GPU ecosystems involving NVIDIA (CUDA/NCCL) or AMD (ROCm/RCCL) in a multi-node setting.
Strong comprehension of networking protocols such as RDMA, RoCE, and InfiniBand in virtualized systems.
Nice to Have
Experience with MNNVL or specialized AI fabric architectures.
Familiarity with hardware-level debugging tools and performance profilers like NVIDIA Nsight and AMD Omniperf.
Knowledge of containerized orchestration for GPUs using Kubernetes with specialized device plugins.
Skills and Tools
Python
Kubernetes
Docker
Terraform
GitLab
Ansible
AWX
Linux
PostgreSQL
Salary and Benefits
Annual compensation ranging between $250,000 and $300,000, plus bonus and Restricted Stock Units
Comprehensive health, dental, and vision insurance with employer HSA contributions
401(k) retirement plan featuring a company match of up to 4% of salary
Paid time off, paid holidays, leave of absence programs, and paid parental leave
Life insurance, short-term and long-term disability protection
Professional development and tuition reimbursement opportunities
Mental health and wellness support, daily meals allowance, cell phone stipend, and commuter benefits
Volunteer time off, global travel insurance, and emergency assistance
About the Company
Crusoe operates as a vertically integrated AI infrastructure company built to power demanding AI workloads with an energy-first approach. By owning and operating every layer of the stack from electrons to tokens, the organization aims to accelerate the abundance of energy and intelligence while solving power bottlenecks in modern computing.
How to Apply
Please visit the official Crusoe careers page to submit your application for this position.
