Production Engineer, Crusoe Energy Systems

• A CS or EE degree, bootcamp, or equivalent hands-on experience, plus genuine interest in infrastructure and systems reliability over application development
• 3 to 5 years of working proficiency in Python or Go. You're comfortable writing and debugging real code, not just shell one-liners
• Familiarity with Linux fundamentals: processes, networking, filesystems, and how hardware and software interact
• Comfort in a fast-paced, high-ownership environment with a real on-call rotation
• Strong communication skills. You'll write incident summaries and work with engineers across compute, storage, and networking, not just your own team
• Curiosity about how distributed systems fail and a habit of asking "why" past the first answer
• Openness to either broad cross-domain work or early specialization in one domain, depending on where the team needs you

Desirable

• This is an entry point into Production Engineering, not a stepping-stone support role
• You'll be one of the engineers keeping a multi-billion dollar, rapidly scaling AI cloud business online, from every GPU cluster to every customer workload and every SLA, while you build the foundational skills that turn into a Senior and Staff-level infrastructure career
• We're hiring several Production Engineer II roles as we build out the next generation of our reliability organization
• We'll determine which team is the best fit for you after the interview process, based on your background, interests, and where your strengths line up with our needs
• The work ranges from broad, cross-domain operations to deeper specialization in compute, storage, or networking, depending on the team
• Triage and resolve production incidents: parse logs, correlate signals across services, and drive issues to root cause using logs, telemetry, and profiling
• Write real automation and tooling in Python or Go to reduce manual toil, including remediation scripts and health checks that catch problems before customers do
• Build and improve monitoring, alerting, observability, and telemetry so the team can see problems before they become incidents
• Participate in on-call rotations, respond to alerts, and contribute to blameless post-mortems
• Work directly with senior and staff engineers on real production engineering problems, and grow into more autonomy quickly
• Depending on Your Team
• Own the health and reliability of production infrastructure supporting Crusoe's AI cloud, whether working cross-domain or going deep in one area
• Build breadth across Crusoe's infrastructure stack and grow toward a specialization (compute, storage, networking, or continued breadth) over time
• On some teams, go deep on one specialization (compute and GPU fleet reliability, storage and distributed storage systems, networking fabric and SDN, Managed AI, Inference, or Managed Cloud)
• On hardware-focused teams, help keep our GPU fleet, including NVIDIA and AMD hardware, running reliably under real production AI workloads
• Run validation testing on configuration changes, firmware updates, and infrastructure modifications before they touch production
• Learn directly from senior and staff engineers who own the hardware and reliability standards for their domain, and grow toward owning more of that surface area yourself