Production Engineer, AI GPU Cloud Reliability & Automation

Crusoe; San Francisco (CA); On-site; USD 172,000 - 209,000; Full time

Benefits offered by this job

Health insurance

401(k) with match

Paid parental leave

Life insurance

Disability insurance

Teladoc

Commuter benefit

Job summary

Crusoe is building a high-performance GPU-focused cloud platform and is seeking a Production Engineer to ensure reliability and scalability of the AI infrastructure. You will lead efforts in incident response, observability, and automation across large-scale systems.

You will collaborate with cross-functional teams to reduce toil, improve SLIs/SLOs, and implement self-healing techniques while growing your technical depth in a dynamic, energy‑driven environment.

Qualifications

• 5+ years of experience in Production Engineering, SRE, or large-scale infrastructure operations.
• Experience supporting GPU workloads, HPC environments, or latency/throughput-sensitive distributed systems.
• Strong knowledge of Linux/Unix systems, including debugging complex issues across kernel and user space.
• Previous experience in Infrastructure roles building or managing compute, storage or networking platforms.
• Understanding of modern cloud infrastructure fundamentals including Kubernetes, distributed systems, virtualization, and cloud platforms (AWS/GCP).
• Familiarity with incident management practices and reliability frameworks (SRE, ITIL, or similar).
• Experience with monitoring and observability tools such as Prometheus and Grafana, or a strong desire to deepen expertise in this area.
• Familiarity with infrastructure-as-code and configuration management tools such as Terraform or Ansible.
• Scripting or programming experience with languages such as Go, Python, C, or C++.
• Strong communication skills and the ability to collaborate across engineering teams.
• Ability to remain calm and effective while troubleshooting complex issues in high-impact production environments.
• A growth mindset and strong interest in reliability engineering, automation, and operational excellence.

Responsibilities

• Collaborate with cross-functional teams on availability metrics for Crusoe’s cloud platform, including SLIs and SLOs.
• Participate in production incident response and perform post-incident reviews.
• Build, operate, and improve observability across Crusoe’s infrastructure using monitoring tools.
• Identify reliability risks and performance bottlenecks in distributed systems.
• Develop automation that reduces operational toil and enables self-healing infrastructure.
• Partner with compute, networking, storage, and platform teams to strengthen service resilience.
• Contribute to improving operational processes and reliability best practices across the engineering org.
• Grow technical depth through mentorship, training, and hands-on work on large-scale AI infrastructure.

Skills

Production Engineering

GPU workloads

Linux/Unix

Infrastructure roles

Kubernetes

Cloud fundamentals (AWS/GCP)

SRE/ITIL familiarity

Monitoring (Prometheus/Grafana)

Infrastructure as code (Terraform/Ansb

Tools

Prometheus

Grafana

Terraform

Ansible

Kubernetes

Job description

Crusoe is building a high-performance GPU-focused cloud platform and is seeking a Production Engineer to ensure reliability and scalability of the AI infrastructure. You will lead efforts in incident response, observability, and automation across large-scale systems.

You will collaborate with cross-functional teams to reduce toil, improve SLIs/SLOs, and implement self-healing techniques while growing your technical depth in a dynamic, energy‑driven environment.