Production Engineer II

Crusoe is on a mission to accelerate the abundance of energy and intelligence

. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.

We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.

We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.

If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.

Start Your Infrastructure Career at the Center of the AI Buildout

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.

What You'll Work On

• 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

What You'll Bring

• 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
• Mindset
• 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, we'll teach you what matters here)
• 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, plus personal projects, open source contributions, or coursework touching distributed systems, low-level systems, or hardware

What This Role Is Not

This is a role that focuses on reliability, not pure Software Engineering

. You won't be building product features. You'll be keeping GPU, storage, or networking infrastructure healthy and reliable under real production load.

Not a role where scripting is optional

. You need working proficiency in Python or Go on day one. Real automation work starts immediately, not after a year of ramping.

Not a help desk or NOC ticket-passing role

. You'll do real engineering: writing automation, debugging distributed systems, and contributing to design discussions.

Not a low-ownership job

. You'll carry on-call and be expected to grow into more autonomy quickly.

Not primarily a Kubernetes or orchestration-tooling job

. Managing a Kubernetes cluster isn't the bar. We're looking for people curious about what's happening below that layer, in the hardware and systems themselves.