Senior Production Engineer, Storage

About This Role

At Crusoe Energy Systems, our Site Reliability Engineering (SRE) team plays a mission-critical role in maintaining the performance and reliability of our AI-optimized cloud infrastructure. The Storage-focused SRE role is responsible for ensuring the availability, performance, and scalability of Crusoe's cloud storage products and services, which power compute-intensive, latency-sensitive workloads for AI and HPC use cases. This role directly supports our vertically integrated, sustainable cloud platform by building and optimizing distributed, fault-tolerant storage systems at scale.

What You'll Be Working On

In this role, you will build automation and self-healing tools to monitor and maintain Crusoe's distributed cloud storage infrastructure, which includes block, file, and object storage systems. You will drive reliability initiatives focused on data replication, encryption, backup and restore strategies, and robust failover mechanisms.

Collaborating closely with storage engineers, you will help implement and maintain high-performance NVMe- and SSD-backed volumes that support large-scale AI compute clusters. Your responsibilities will also include supporting user-facing storage services with a focus on availability, performance tuning, and adherence to error budgets.

You'll investigate and resolve storage-related incidents using deep telemetry, logs, and performance profiling, while also partnering with hardware and kernel teams to diagnose low-level I/O issues and optimize I/O paths, cache policies, and file systems. Additionally, you will contribute to the architecture of fault-tolerant, scalable storage backends tailored for AI-first cloud environments.

What You'll Bring to the Team

• Bachelor's degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience
• 5+ years of professional experience in Storage SRE, systems, or storage engineering
• Deep, hands-on experience with enterprise storage platforms such as Pure Storage or EMC - not limited to volume creation/provisioning, but a working understanding of how the systems are architected and operated
• Deep understanding of object, block, and file storage paradigms
• Proficiency in a programming language such as Go, Python, Java, or C
• Experience with Infrastructure as Code and deployment tooling such as Terraform, Ansible, or Puppet
• Deep knowledge of Linux internals with a focus on I/O subsystems, memory management, and storage scheduling
• Familiarity with storage protocols like NFS, SMB, iSCSI, or NVMe-oF
• Strong experience working with containerized workloads and orchestration platforms (e.g., Kubernetes, Docker)
• Excellent incident response, troubleshooting, and documentation practices
• Experience with building and operating managed services at scale such as object, file and block storage (AWS, GCP, Azure)

Nice to Have

• Hands-on experience with distributed storage systems (e.g., Ceph, GlusterFS, OpenEBS, Vast, Lightbits)
• Contributions to open-source storage projects or the Linux storage stack
• Experience with hybrid storage models across on-prem and cloud environments

Benefits

• Industry competitive pay
• Restricted Stock Units in a fast growing, well-funded technology company
• Health insurance package options that include HDHP and PPO, vision, and dental for you and your dependents
• Employer contributions to HSA accounts
• Paid Parental Leave
• Paid life insurance, short-term and long-term disability
• Teladoc
• 401(k) with a 100% match up to 4% of salary
• Generous paid time off and holiday schedule
• Cell phone reimbursement
• Tuition reimbursement
• Subscription to the Calm app
• MetLife Legal
• Company paid commuter benefit; $300 per month

Compensation

Compensation will be paid in the range of $170,000 - $205,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data.