Infrastructure Engineer (Storage)

Lightning AI • Seattle, WA

1d • Hybrid

About The Position

Lightning AI is seeking a Senior Storage Infrastructure Engineer to join their Infrastructure Engineering team. In this role, you will focus on building and operating the storage systems that power large-scale AI/ML training, inference, and HPC workloads. You will work at the intersection of software, hardware, and operations—developing automation, improving reliability, and scaling distributed storage systems across their bare-metal infrastructure. You will help own the data plane of their storage infrastructure, supporting high-throughput, low-latency data access for some of the most demanding AI workloads. You’ll play a key role in managing and evolving their storage stack (including VAST and S3-compatible systems like Ceph), ensuring performance, reliability, and efficiency at scale. This role can work hybrid out of one of their US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. Visa sponsorship is not available for this position.

Requirements

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Hands-on experience operating distributed storage systems (e.g., VAST, Ceph, or similar)
• Strong Linux systems experience in production environments
• Proficiency in Python or similar scripting/programming languages for automation
• Experience working with bare-metal infrastructure and hardware-oriented systems
• Ability to debug complex issues across system boundaries (storage, OS, hardware, networking)
• Experience with storage networking protocols (e.g., NFS or similar)
• Experience with capacity planning, monitoring, and performance tuning

Nice To Haves

• Experience with VAST storage systems in production environments
• Experience operating S3-compatible object storage at scale
• Data center operations experience, including working with physical hardware
• Familiarity with AI/ML or HPC workloads and their storage requirements
• Background in high-performance or low-latency distributed systems
• Familiarity with high-performance data transfer technologies (e.g., RDMA, GPU Direct Storage)
• Experience supporting GPU-based workloads or large-scale compute clusters

Responsibilities

• Operate and scale distributed storage systems, including VAST and S3-compatible object storage (e.g., Ceph)
• Improve performance, reliability, and efficiency of storage systems supporting large-scale AI/ML workloads
• Troubleshoot complex storage and data path issues across hardware and software layers
• Optimize storage performance to support high-throughput, low-latency AI training and inference workloads
• Build and maintain automation for provisioning, managing, and monitoring storage infrastructure
• Develop Python-based tools and workflows to reduce manual operational overhead
• Improve lifecycle management of storage clusters, from deployment through maintenance and scaling
• Manage and operate Linux-based systems in production, including bare-metal environments
• Partner with infrastructure and data center teams on hardware bring-up, upgrades, and issue resolution
• Support capacity planning, utilization tracking, and forecasting for storage systems
• Leverage monitoring and telemetry to diagnose issues and improve system performance and reliability
• Work closely with Infrastructure Engineering, Network Engineering, and Platform teams to integrate storage into the broader platform
• Contribute to design discussions around new infrastructure deployments and scaling strategies
• Help define best practices for operating storage systems in high-performance computing environments

Benefits

• Comprehensive medical, dental and vision coverage (U.S.); Private medical and dental insurance (U.K.)
• Retirement and financial wellness support (U.S.); Pension contribution (U.K.)
• Generous paid time off, plus holidays
• Paid parental leave
• Professional development support
• Wellness and work-from-home stipends
• Flexible work environment
• Discretionary bonus
• Meaningful equity component

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed