Senior Network Engineer
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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 Senior Network Engineer with hands-on Cumulus Linux expertise to build and scale the network backbone behind our AI infrastructure platform. You’ll play a critical role in designing highly reliable, automated data center networks that support some of the most demanding AI workloads in the world.
This role is hybrid out of our San Francisco, Seattle, or NYC offices, fully remote within the U.S. All employees participate in occasional team and company offsites.
What You'll Do
- Design and deploy scalable spine/leaf network architectures for AI data centers
- Engineer high-performance Ethernet fabrics supporting GPU clusters and AI workloads
- Build and maintain EVPN/VXLAN, BGP, and high-speed routing environments
- Optimize east-west traffic flows for AI training and inference operations
- Support RoCE/RDMA networking and low-latency transport technologies
- Support backbone, DCI, WAN, and edge connectivity solutions.
- Collaborate with compute, storage, AI platform, and operations teams to deliver integrated infrastructure solutions
- Develop automation and Infrastructure-as-Code (IaC) solutions for network provisioning and operations
- Troubleshoot complex network, performance, and congestion issues across distributed environments
- Improve network observability, telemetry, and operational visibility
- You have hands-on experience working with SONiC and Junos.
- Experience with cloud networking technologies including VPC’s, NFV, Direct Connect, Cloud Connect
- You enjoy working with a small group of friendly, highly motivated, high-execution colleagues
- You’re comfortable with a high degree of autonomy, can independently prioritize your work and understand how it maps to the overall needs and goals of the company
- You’re knowledgeable in your domain but also enjoy wearing multiple hats and venturing outside of your comfort zone when the need arises
- You value the ability to write well and understand the importance of good documentation
What You’ll Need Required Qualifications
- Experience with Cumulus NOS
- 5+ years of experience in large-scale...
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About Lightning AI
Learn more about Lightning AI and their company culture.
Developer platform behind PyTorch Lightning for building, training and deploying AI systems, with GPU compute.
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