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Salary: USD 140,000 - 165,000 / annual
Crusoe is a vertically integrated AI infrastructure company building the energy and compute backbone for the world's most ambitious AI workloads. They own and operate every layer of the stack—from electrons to tokens—with an energy-first approach to power AI at scale.
You'll join the reliability organization as a Production Engineer II, one of several new hires building out the next generation of infrastructure operations. This is a true entry point into production engineering, not a support role. You'll be responsible for keeping Crusoe's multi-billion-dollar, rapidly scaling AI cloud business online—from GPU clusters to customer workloads to SLAs—while building foundational skills that lead to Senior and Staff-level infrastructure careers.
The work ranges from broad, cross-domain operations to deeper specialization in compute, storage, or networking, depending on which team is the best fit for your background and interests.
Key Responsibilities:
• Triage and resolve production incidents by parsing logs, correlating signals across services, and driving 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, growing into more autonomy quickly
• Own the health and reliability of production infrastructure supporting Crusoe's AI cloud, either working cross-domain or going deep in one area
• Build breadth across Crusoe's infrastructure stack and grow toward specialization (compute, storage, networking, or continued breadth) over time
• On hardware-focused teams, help keep GPU fleets (NVIDIA and AMD) 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 hardware and reliability standards for their domain
Requirements:
• 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; 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
• 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
Nice to Have:
• Exposure to Kubernetes or container orchestration (not required)
• Exposure to GPUs, HPC environments, kernel internals, or systems and validation engineering coursework or projects
• Prior on-call, NOC, IT ops, or lab/systems administration experience; personal projects, open source contributions, or coursework touching distributed systems, low-level systems, or hardware
