Senior Production Engineer (Core PE)

• Crusoe is building the most reliable, energy-efficient, AI-optimized cloud platform — and Production Engineering sits at the heart of that mission. As a Production Engineer focused on Operational Excellence, you will help ensure the reliability, scalability, and performance of Crusoe’s GPU cloud that powers next-generation AI workloads
• This role is ideal for engineers who enjoy solving complex production problems, improving large-scale distributed systems, and building automation that keeps infrastructure running smoothly. You’ll play a key role in strengthening the operational foundation of Crusoe’s cloud while helping scale infrastructure that supports demanding AI and HPC workloads
• You’ll partner closely with Production Engineers, infrastructure teams, and platform engineers to improve system reliability, reduce operational toil, and drive continuous improvements across Crusoe’s rapidly growing GPU cloud
• Collaborate with cross-functional teams to define and evolve availability metrics for Crusoe’s cloud platform, including establishing, measuring, and improving SLIs and SLOs
• Participate in production incident response, diagnosing and resolving service disruptions while contributing to post-incident reviews and root cause analysis
• Build, operate, and improve observability across Crusoe’s infrastructure using tools such as Prometheus, Grafana, Alertmanager, and OpenTelemetry
• Identify reliability risks, performance bottlenecks, and early indicators of potential production issues across distributed systems
• Develop automation and tooling that reduces operational toil, improves recovery times, and enables self-healing infrastructure
• Partner with compute, networking, storage, and platform teams to strengthen service resilience and disaster recovery capabilities
• Contribute to improving operational processes, knowledge sharing, and reliability best practices across the engineering organization
• Continue growing technical depth through mentorship, training, and hands-on work operating large-scale AI infrastructure

Benefits

• Health & wellbeing: Comprehensive health benefits designed to support your overall wellness
• Time away: Paid time off for vacations, family bonding, and unexpected needs
• 401(k) match: Build your financial future with our 401(k) matching program
• Mental wellness: Resources and support for your emotional wellbeing and navigating life’s challenges

• Understanding of modern cloud infrastructure fundamentals including Kubernetes, distributed systems, virtualization, and cloud platforms (AWS/GCP)
• Experience with monitoring and observability tools such as Prometheus and Grafana, or a strong desire to deepen expertise in this area
• Experience supporting GPU workloads, HPC environments, or latency/throughput-sensitive distributed systems
• Familiarity with infrastructure-as-code and configuration management tools such as Terraform or Ansible
• A growth mindset and strong interest in reliability engineering, automation, and operational excellence
• 5+ years of experience in Production Engineering, SRE, or large-scale infrastructure operations
• Previous experience in Infrastructure roles building or managing compute, storage or networking platforms
• Ability to remain calm and effective while troubleshooting complex issues in high-impact production environments
• Familiarity with incident management practices and reliability frameworks (SRE, ITIL, or similar)
• Strong communication skills and the ability to collaborate across engineering teams
• Scripting or programming experience with languages such as Go, Python, C, or C++
• Strong knowledge of Linux/Unix systems, including debugging complex issues across kernel and user space
• Interest in scaling AI or HPC infrastructure and solving reliability challenges in GPU-heavy environments
• Passion for mentorship, learning, and developing deeper expertise in Production Engineering
• Experience designing self-healing systems, automated remediation, or event-driven operational tooling
• Experience working with Kubernetes or container orchestration platforms at scale
• Exposure to change management processes, operational readiness reviews, or structured root cause analysis