Staff Software Engineer (DC Infrastructure)

Join Crusoe's Data Center Infrastructure Engineering team as a Staff Software Engineer. In this role, you will develop software for managing a fleet of GPU servers and the data centers that house them. You will focus on advanced diagnostics, observability, automation, and repair tooling for high-performance GPU compute clusters. You will also work on troubleshooting and automation tooling for various GPU platforms, develop AI agents for hardware diagnosis and remediation, and create tooling for post-repair validation and testing. Additionally, you will own the deployment, monitoring, and operational support of developed tooling, ensuring maximum GPU fleet availability and performance.

• Develop and implement advanced diagnostic, observability, automation, and repair tooling for high-performance GPU compute clusters.
• Develop troubleshooting and automation tooling for GPU platforms including NVIDIA A100, H200, GB200, B200 and AMD 350X / 355X.
• Own the deployment, monitoring, and operational support of developed tooling, ensuring solutions maximize GPU fleet availability and performance.

• The ideal new team member will be a hands-on problem solver who is comfortable working independently. The new team member will play a critical role in maintaining the health and scalability of Crusoe’s rapidly growing GPU fleet
• Ability to work independently and within a team
• Strength in at least one programming language - Go, Python, Java, Rust
• Strong analytical and problem-solving skills
• Software engineering experience
• Excellent communication and collaboration skills
• Expertise in distributed systems, reliability, and cloud platforms (Kubernetes, IaC, GCP etc.)
• The ability to identify a problem, rapidly develop a scalable solution and ship it
• Ability to set the technical direction for a specific project and execute
• Ability to lean in and assist team members working on critical or complex technical initiatives
• Experience with Temporal and Kubernetes
• Experience working directly with hardware vendors
• Background in large-scale GPU fleet operations or hyperscale data center environments