Senior Automation Engineer, Crusoe Energy Systems

• Education & Experience: 5+ YOE demonstrated ability to competently and independently perform responsibilities plus 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
• A 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
• CI/CD & Gitlab: Intimate knowledge of CI/CD pipelines and Gitlab Tooling to enable stable infrastructure releases across multiple datacenters
• Configuration Management: Previous experience with at least 1-2 configuration management systems, including Ansible, Puppet, Chef, or SaltStack
• System Internals: Knowledge of Linux kernel internals, specifically PCIe topology, VFIO, and memory management (HugePages, IOMMU)

Desirable

• As a Senior Deployment Automation Engineer for the Compute Team, you will be responsible for deployment and testing automation of large-scale, multi-node GPU clusters
• You will develop the CI/CD infrastructure, including both deployment and integration testing, for a rapidly scaling fleet of virtualized GPU and CPU hosts across our AI Cloud
• Your role is critical in ensuring the stability of the low-level infrastructure and enabling teams across our Cloud Infrastructure organization to quickly and reliably release, test, and deploy their artifacts across our datacenters
• Deployment and Integration Testing: Develop applications and systems for deployment and integration testing on bare-metal, on-premise systems across Crusoe’s AI Cloud Stack
• CI/CD Automation and Tooling: Build CI/CD platforms that enable developers to quickly test, iterate, and deploy critical, low-level systems and applications
• Multi-Node Scaling Validation: Design and execute large-scale validation tests across multi-node virtualized clusters to ensure linear scaling and stability of GPU workloads
• Configuration Management and Observability: Maintain and scale bare-metal Linux configurations using a mix of custom and off the shelf tooling such as Gitlab, Ansible, osquery, etc
• Deployment Orchestration: Create control applications to coordinate canary deployments on live production systems, run Blue/Green testing, and perform automatic rollback where necessary
• Cluster Orchestration: Develop and maintain automation frameworks in Python or Go to dynamically provision, configure, and stress-test multi-node virtualized environments
• Create automated test suites leveraging tools like fio, stress-ng, and iperf to ensure performance and multi-tenant isolation of CPU and GPU hosts