Remote Storage Infrastructure Engineer — High-Performance

lightningai; United States; Hybrid; USD 180,000 - 220,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

Retirement matching

Unlimited PTO

Company offsites

Sabbatical after four years

Learning & development allowance

Wellness stipend

Work-from-home stipend

Meal benefits

Flexible schedules

Job summary

lightningai is seeking a Storage Infrastructure Engineer to own the data plane of its distributed storage stack. You will operate high-throughput, low-latency storage on bare-metal infrastructure, interfacing with data center teams on hardware bring-up and upgrades.

The role emphasizes automation, reliability, and scaling of production systems, with a focus on AI/ML workloads. A strong background in Linux, Python, and large-scale storage is required.

Qualifications

• 5+ years in infrastructure engineering or related field.
• Hands-on experience operating distributed storage systems at scale (VAST, Ceph).
• Strong Linux systems experience in production environments.
• Proficiency in Python or comparable scripting for automation.

Responsibilities

• Operate and scale distributed storage systems (VAST, Ceph).
• Troubleshoot storage and data-path issues across hardware, OS, and software layers.
• Build Python automation for provisioning, lifecycle management, and monitoring of storage clusters.
• Manage Linux-based production systems in bare-metal environments with data center collaboration.
• Support capacity planning, utilization tracking, and forecasting using monitoring/telemetry.
• Collaborate with infrastructure, network, and platform teams on high-performance storage designs.

Skills

Infrastructure engineering

Python scripting

Linux administration

Distributed storage

Tools

Ceph

VAST

Job description

lightningai is seeking a Storage Infrastructure Engineer to own the data plane of its distributed storage stack. You will operate high-throughput, low-latency storage on bare-metal infrastructure, interfacing with data center teams on hardware bring-up and upgrades.

The role emphasizes automation, reliability, and scaling of production systems, with a focus on AI/ML workloads. A strong background in Linux, Python, and large-scale storage is required.