Production Engineer II
Crusoe · San Francisco, CA - US
About this role
## Production Engineer II — Crusoe Crusoe is on a mission to accelerate the abundance of energy and intelligence. As a vertically integrated AI infrastructure company, we own and operate each layer of the stack—from electrons to tokens—to power the world’s most ambitious AI workloads. This **Production Engineer II** role is an **entry point into Production Engineering** (not a support/help-desk role). You’ll help keep a rapidly scaling AI cloud business online—across GPU clusters, customer workloads, and SLAs—while building foundational skills for a future **Senior/Staff infrastructure career**. --- ## 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 automation and tooling in Python or Go** to reduce manual toil (e.g., remediation scripts and health checks) - **Build and improve monitoring/alerting/observability/telemetry** so problems are visible before they become incidents - **Participate in on-call rotations**, respond to alerts, and contribute to blameless post-mortems - Work with **senior and staff engineers** on real production engineering problems and grow into more autonomy quickly --- ## Depending on Your Team You may: - Own the **health and reliability** of production infrastructure (cross-domain or deep specialization) - Build breadth across Crusoe’s infrastructure stack, then specialize over time in **compute, storage, or networking** - On some teams, go deep in areas like **compute/GPU fleet reliability, storage/distributed storage, networking fabric/SDN, Managed AI, inference, or managed cloud** - On hardware-focused teams, help keep the **GPU fleet** (NVIDIA and AMD) running reliably under real production AI workloads - Run validation testing on **configuration changes, firmware updates, and infrastructure modifications** before they reach production --- ## What You’ll Bring - **CS or EE degree**, bootcamp, or equivalent hands-on experience; genuine interest in **infrastructure and systems reliability** - **3–5 years** of working proficiency in **Python or Go** (comfortable writing and debugging real code) - Familiarity with **Linux fundamentals** (processes, networking, filesystems, and hardware/software interaction) - Comfort in a **fast-paced, high-ownership** environment with a real **on-call rotation** - Strong communication skills (incident summaries; collaboration across compute/storage/networking) - A mindset of **curiosity** about distributed systems failure and a habit of asking “why” - Openness to **broad cross-domain work** or early specialization based on team needs --- ## Nice to Have - Exposure to **Kubernetes/container orchestration** (not required) - Exposure to **GPUs, HPC environments, kernel internals**, or systems/validation engineering coursework/projects - Prior **on-call**, NOC, IT ops, lab/systems administration experience - Personal projects, open source contributions, or coursework related to distributed systems, low-level systems, or hardware --- ## What This Role Is Not - Not pure software/product feature development - Not a role where scripting is optional (you need **Python/Go proficiency on day one**) - Not a help desk or ticket-passing role - Not primarily Kubernetes/orchestration-tooling (we care about what’s happening below that layer) - Not low-ownership—expect on-call and growing autonomy --- ## Benefits (Highlights) - Industry co
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