Senior Software Engineer — GPU Data Center Automation

Crusoe; San Francisco (CA); On-site; USD 170,000 - 205,000; Full time

Benefits offered by this job

Health insurance package options

Restricted Stock Units

401(k) with match up to 4%

Paid parental leave

Teladoc

Job summary

Crusoe is on a mission to accelerate the abundance of energy and intelligence. We are seeking a Software Engineer to join Crusoe’s Data Center Infrastructure Engineering team, focusing on software for managing a fleet of GPU servers and the data centers that house them.

You will build advanced diagnostics, observability, automation and repair tooling for high‑performance GPU compute clusters. The successful candidate will be hands-on, independent, and pivotal in maintaining health and

Qualifications

• 4-6 years of software engineering experience.
• Experience with distributed systems, reliability and cloud platforms.
• Proficient in Go, Python, Java or Rust.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.
• Ability to work independently and within a team.

Responsibilities

• Develop deep-level diagnostics and troubleshooting for GPU racks and high-density compute systems.
• Build automation tooling for GPU platforms (NVIDIA A100, H200, GB200, B200; AMD 350X/355X).
• Create automation and AI agents for component-level diagnosis and remediation.
• Collaborate with data center operations to develop tooling and AI agents for critical environments.
• Develop post-repair validation and testing tools (burn-in, PyTorch, NVIDIA NCCL).
• Own deployment, monitoring and operational support of tooling to maximize GPU fleet availability.
• Develop automation and operational tooling for facilities management power and liquid cooling systems.

Skills

Distributed systems

Cloud platforms

Kubernetes

Go

Python

Java

Rust

Teamwork

Problem solving

Job description

Crusoe is on a mission to accelerate the abundance of energy and intelligence. We are seeking a Software Engineer to join Crusoe’s Data Center Infrastructure Engineering team, focusing on software for managing a fleet of GPU servers and the data centers that house them.

You will build advanced diagnostics, observability, automation and repair tooling for high‑performance GPU compute clusters. The successful candidate will be hands-on, independent, and pivotal in maintaining health and