Senior Staff Deployment Automation Engineer

Responsibilities

• Own deployment and integration testing automation for bare-metal, on-premise systems across the AI Cloud stack.
• Build CI/CD platforms that enable rapid testing, iteration, and deployment of low-level systems and applications.
• Design and execute large-scale validation tests across multi-node virtualized clusters to verify GPU workload scaling and stability.
• Maintain and scale bare-metal Linux configurations using GitLab, Ansible, AWX, osquery, and related tooling.
• Create control applications for canary deployments, blue/green testing, and automated rollback on production systems.
• Develop automation frameworks in Python or Go to provision, configure, and stress-test multi-node virtualized environments.
• Build automated test suites with fio, stress-ng, and iperf to validate performance and CPU/GPU host isolation.

Requirements

• 12+ years of professional experience performing comparable responsibilities independently.
• Bachelor's or master's degree in Computer Science, Electrical Engineering, or a related technical field.
• Experience building and deploying automated integration testing for AI cloud environments, from low-level Linux systems through distributed control planes.
• Working knowledge of Kubernetes, Docker, Terraform, and PostgreSQL.
• Extensive knowledge of CI/CD pipelines and GitLab tooling across multiple datacenters.
• Experience with one or more configuration management systems, such as Ansible, Puppet, Chef, or SaltStack.
• Advanced Python and/or Bash proficiency for complex cluster-wide automation.
• Knowledge of Linux kernel internals, including PCIe topology, VFIO, HugePages, and IOMMU.
• Familiarity with NVIDIA CUDA/NCCL and/or AMD ROCm/RCCL in multi-node environments.
• Strong understanding of RDMA, RoCE, and InfiniBand in virtualized systems.

Nice-to-haves

• Experience with MNNVL or specialized AI fabric architectures.
• Familiarity with hardware debugging tools and performance profilers such as NVIDIA Nsight and AMD Omniperf.
• Knowledge of GPU container orchestration, including Kubernetes device plugins.

Compensation and Benefits

• Compensation of up to $250,000–$300,000, plus bonus.
• Restricted Stock Units included in offers.
• Paid time off, holidays, and leave programs.
• Health, dental, and vision insurance.
• Employer HSA contributions.
• Paid parental leave, life insurance, and short- and long-term disability coverage.
• Professional development and tuition reimbursement.
• Mental health and wellness support.
• Commuter benefits and cell phone stipend.
• 401(k) plan with company match up to 4% of salary.
• Volunteer time off, global travel insurance, emergency assistance, daily meals allowance, and location-specific programs.