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Salary analysis
Compared with the selected benchmark ("Company in London, United Kingdom"), this listing's salary midpoint is about 3% lower. The offer still falls within the benchmark range (€11,936–€22,426). The listed pay band (€15,000–€18,333) is tighter than the benchmark, which suggests lower salary variability. This benchmark is based on 1 comparable listings.
| Market | Lower bound (25th percentile) | Median | Upper bound (75th percentile) |
|---|---|---|---|
| All roles in London, United Kingdom | €4,030/per month | €9,310/per month | €15,737/per month |
| Company in London, United Kingdom | €11,936/per month | €17,181/per month | €22,426/per month |
Lightning AI is seeking a Storage Infrastructure Engineer to join our 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 our bare-metal infrastructure. You’ll help own the data plane of our 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 our storage stack (including VAST and S3-compatible systems like Ceph), ensuring performance, reliability, and efficiency at scale. This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.
Job Details
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
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)
Skills & Technologies
| Location | Active listings |
|---|---|
| London, United Kingdom | 1 |
| New York, United States | 1 |
| San Francisco, United States | 1 |
| Seattle, United States | 1 |
| Remote - Global | 1 |
| Role type | Active listings |
|---|---|
| Research Engineer | 1 |
| Role level | Active listings |
|---|---|
| Mid-Level | 1 |
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