At a Glance
- Tasks: Build and operate cutting-edge storage systems for AI/ML workloads.
- Company: Join Lightning AI, a leader in AI development and deployment.
- Benefits: Competitive salary, equity options, unlimited PTO, and wellness benefits.
- Other info: Dynamic work environment with opportunities for professional growth.
- Why this job: Make an impact in the fast-paced world of AI technology.
- Qualifications: 5+ years in infrastructure engineering with strong Linux and Python skills.
The predicted salary is between 80000 - 98000 £ per year.
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 forecasting for storage systems. Leverage monitoring and telemetry to diagnose issues and improve system performance and reliability.
- Cross-Functional Collaboration: 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.
What You'll Need
Required Qualifications:
- 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.
Ideal Experience:
- 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.
Compensation
We are committed to offering competitive compensation that reflects the value each team member brings to our mission. Final offers are based on factors such as experience, skills, geographic location, and role expectations. In addition to base salary, our total rewards package for eligible roles includes a discretionary bonus, a meaningful equity component, and comprehensive benefits. The anticipated annual base salary range for this role is: $180,000—$220,000 USD.
Benefits and Perks
We offer a comprehensive and competitive benefits package designed to support our employees’ health, well-being, and long-term success:
- Comprehensive Health Coverage: Medical, dental, and vision coverage for employees and eligible dependents.
- Meaningful Equity: RSUs that give employees a stake in the company's long-term success.
- Retirement Savings: 401(k) matching (U.S.) and pension contributions (U.K.).
- Flexible Time Off: Unlimited PTO, company holidays, and floating holidays to support work-life balance.
- Company-Wide Winter Break: Two weeks of company closure each winter to disconnect and recharge.
- Paid Parental & Family Leave: Paid leave to support you and your family through life's important moments.
- Professional Development: Annual learning and development allowance to support your professional growth.
- Wellness Benefits: Wellness and other benefits.
Infrastructure Engineer (Storage) employer: Lightning AI
Lightning AI is an exceptional employer that fosters a collaborative and inclusive work culture, where innovation thrives and employees are empowered to take ownership of their projects. With offices in vibrant cities like London, our team enjoys a flexible work environment, comprehensive benefits, and ample opportunities for professional growth, making it an ideal place for passionate Backend Engineers to advance their careers while contributing to cutting-edge AI technology.
StudySmarter Expert Advice🤫
We think this is how you could land Infrastructure Engineer (Storage)
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Lightning AI or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Lightning AI.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Lightning AI.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Lightning AI that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Infrastructure Engineer (Storage)
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Lightning AI.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Lightning AI and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Lightning AI
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Lightning AI uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.