Staff Production Engineer (Core PE)

Join Crusoe, a company dedicated to building the most reliable, energy-efficient, AI-optimized cloud platform. As a Staff Production Engineer, you will play a key role in ensuring the reliability, scalability, and performance of Crusoe's GPU cloud. You will lead cross-functional efforts to define and evolve availability metrics, drive production incident response, and improve observability across the infrastructure. This role is ideal for senior engineers who enjoy solving complex production problems and building automation to keep infrastructure running smoothly.

• Lead cross-functional efforts to define and evolve availability metrics for Crusoe's cloud platform, including establishing, measuring, and improving SLIs and SLOs.
• Drive production incident response, diagnosing and resolving service disruptions while leading post-incident reviews and root cause analysis.
• Architect, operate, and improve observability across Crusoe's infrastructure using tools such as Prometheus, Grafana, Alertmanager, and OpenTelemetry.

• Deep knowledge of Linux/Unix systems, including debugging complex issues across kernel and user space
• A growth mindset and strong commitment to reliability engineering, automation, and operational excellence
• Experience with infrastructure-as-code and configuration management tools such as Terraform or Ansible
• Ability to remain calm and effective while troubleshooting complex issues in high-impact production environments
• Exceptional communication skills and the ability to influence and collaborate across engineering teams
• 8+ years of experience in Production Engineering, SRE, or large-scale infrastructure operations
• Proven track record with incident management practices and reliability frameworks (SRE, ITIL, or similar)
• Hands-on experience with monitoring and observability tools such as Prometheus and Grafana
• Proficiency in scripting or programming with languages such as Go, Python, C, or C++
• Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
• Demonstrated experience supporting GPU workloads, HPC environments, or latency/throughput-sensitive distributed systems
• Strong understanding of modern cloud infrastructure fundamentals including Kubernetes, distributed systems, virtualization, and cloud platforms (AWS/GCP)
• Experience leading Kubernetes or container orchestration platforms at scale
• Exposure to change management processes, operational readiness reviews, or structured root cause analysis
• Experience designing self-healing systems, automated remediation, or event-driven operational tooling
• Interest in scaling AI or HPC infrastructure and solving reliability challenges in GPU-heavy environments
• Passion for mentorship, growing teams, and developing deep expertise in Production Engineering