Senior Software Engineer (DCIE)

Crusoe Energy Systems; San Francisco (CA); On-site; USD 180,000 - 300,000; Full time

Benefits offered by this job

Health benefits

Paid time off

401(k) match

Mental wellness resources

Job summary

Crusoe Energy Systems is seeking a Software Engineer to join the Data Center Infrastructure Engineering team. You will develop software for managing a fleet of GPU servers and the data centers housing them, building diagnostics, observability, automation, and repair tooling for high-density compute clusters.

The role emphasizes hands-on problem solving, independence, and helping scale Crusoe's GPU fleet with robust tooling and AI-assisted diagnostics across NVIDIA and AMD platforms.

Qualifications

• 4–6 years of software engineering experience.
• Strong in at least one programming language (Go, Python, Java, Rust).
• Experience with distributed systems, reliability, and cloud platforms.
• Experience with Kubernetes and Temporal.
• Experience working with hardware vendors and GPU fleet operations.

Responsibilities

• Develop software for managing a fleet of GPU servers and data centers.
• Build advanced diagnostic, observability, automation, and repair tooling for GPU clusters.
• Own deployment, monitoring, and operational support of tooling to maximize fleet availability and performance.
• Collaborate with data center operations to create tooling for facilities management including cooling.

Skills

Go

Python

Java

Rust

Distributed systems

Kubernetes

GCP

Tools

Temporal

Kubernetes

Infrastructure as Code

NVIDIA NCCL

Job description

• We are seeking a highly skilled and motivated Software Engineer to join Crusoe’s Data Center Infrastructure Engineering team
• This position is focused on the development of software for the management of a fleet of GPU servers as well as the data centers that house those systems
• The role focuses on the developing and implementing advanced diagnostic, observability, automation and repair tooling for high-performance GPU compute clusters
• 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
• Developing and implementing deep-level diagnostics and troubleshooting of hardware faults within GPU racks and high-density compute systems
• Developing troubleshooting and automation tooling for GPU platforms including NVIDIA A100, H200, GB200, B200 and AMD 350X / 355X
• Developing automation and AI agents for executing component-level diagnosis and remediation for failed or degraded hardware
• In conjunction with data center operations develop innovative tooling and AI agents for managing the critical environment
• Developing tooling for post-repair validation and testing tools such as burn-in, Pytorch, and NVIDIA NCCL to ensure system stability and performance
• Own the deployment, monitoring, and operational support of developed tooling, ensuring solutions maximize GPU fleet availability and performance to drive customer success
• Developing automation and operational tooling for facilities management power as well as direct liquid cooling hardware systems

Benefits

• Health & wellbeing: Comprehensive health benefits designed to support your overall wellness
• Time away: Paid time off for vacations, family bonding, and unexpected needs
• 401(k) match: Build your financial future with our 401(k) matching program
• Mental wellness: Resources and support for your emotional wellbeing and navigating life’s challenges

• Ability to lean in and assist team members working on critical or complex technical initiatives
• Ability to work independently and within a team
• Strong analytical and problem-solving skills
• Ability to set the technical direction for a specific project and execute
• The ability to identify a problem, rapidly develop a scalable solution and ship it
• 4-6 years of software engineering experience
• Strength in at least one programming language - Go, Python, Java, Rust
• Expertise in distributed systems, reliability, and cloud platforms (Kubernetes, IaC, GCP etc.)
• Excellent communication and collaboration skills
• Experience with Temporal and Kubernetes
• Experience working directly with hardware vendors
• Background in large-scale GPU fleet operations or hyperscale data center environments