Infrastructure Engineer (Storage)
Lightning AI
| Company | Lightning AI |
| Category | Engineering |
| Location | London |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 1 May 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Who We Are
Lightning AI is the company behind PyTorch Lightning. Founded in 2019, we build an end-to-end platform for developing, training, and deploying AI systems—designed to take ideas from research to production with less friction.
Through our merger with Voltage Park, a neocloud and AI Factory, Lightning AI combines developer-first software with cost-efficient, large-scale compute. Teams get the tools they need for experimentation, training, and production inference, with security, observability, and control built in.
We serve solo researchers, startups, and large enterprises. Lightning AI operates globally with offices in New York City, San Francisco, Seattle, and London, and is backed by Coatue, Index Ventures, Bain Capital Ventures, and Firstminute.
The Way We Work
The people who thrive here are builders who move fast, communicate openly, take ownership, and continuously improve themselves, their teams, and our company. Here's what that looks like in practice:
Move with Urgency: We move quickly, make thoughtful decisions, and keep momentum. We value action over perfection and learn by shipping.
Take Ownership: We own outcomes, not just our individual work. We make decisions that move the company forward and follow through.
Communicate Openly: We communicate directly, seek to understand, and create clarity for others. Honest conversations help us move faster together.
Build Great Teams: We lead by example, empower others, and create healthy teams where people can do their best work.
Raise the Bar: We're always improving ourselves. We learn from feedback, consistently challenge ourselves to grow, and focus on the work that matters most.
Think Long-Term: We design for what's next. We create scalable systems, simplify complexity, and use AI and automation to amplify our impact.
What We're Looking For
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 will 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.
What You'll Do
Storage Systems & Infrastructure
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
Automation & Tooling
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
Systems & Operations
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 fo
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