At a Glance
- Tasks: Design and own network architecture for cutting-edge GPU AI infrastructure.
- Company: Stealth AI infrastructure company revolutionising GPU compute for frontier AI customers.
- Benefits: Competitive salary, flexible work options, and opportunities to shape the future of AI.
- Other info: Join a dynamic team and set standards for future engineers in an ambitious project.
- Why this job: Be a pioneer in building AI factories and make a significant impact on the industry.
- Qualifications: Experience with GPU deployments, InfiniBand, and multi-vendor networking.
The predicted salary is between 80000 - 100000 € per year.
We are hiring a Senior Network Architect for a stealth AI infrastructure company building large scale GPU compute infrastructure for frontier AI customers. This is not a standard data centre networking role. The company is building AI factories at industrial scale, where the network fabric is as critical as the compute itself. A routing issue, congestion event or weak fabric design can directly impact customer training workloads.
This person will own network architecture across GPU fabric, InfiniBand, RoCE v2, Ethernet leaf spine, edge connectivity, peering, observability, deployment standards and operational handover.
We are looking for someone who has:
- Deep GPU cluster or HPC deployment experience
- Strong InfiniBand production experience
- RoCE v2 experience at scale
- Ethernet fabric experience across BGP, ECMP and low latency operations
- IPv6 and public ASN experience
- Multi vendor experience across environments such as NVIDIA Mellanox, Arista, Juniper, Cisco, whitebox or ODM hardware
- Experience from a neo cloud, hyperscaler, major vendor, GPU infrastructure company, HPC platform or AI infrastructure provider
Must haves:
- You must have worked on real GPU deployments
- You must have multi vendor network experience
- You must come from a relevant AI infrastructure, hyperscale, vendor or HPC environment
Single vendor specialists or traditional enterprise networking profiles will not be the right fit. This is the first senior network hire and will set the standards future engineers build and operate against.
If you have built, deployed or operated network fabrics for serious GPU infrastructure, this is a rare opportunity to shape the foundation of one of the most ambitious AI infrastructure builds in the market.
Senior Network Architect, GPU Fabric and AI Infrastructure in London employer: WNTD
Join a pioneering AI infrastructure company that is redefining the landscape of GPU compute technology. As a Senior Network Architect, you will be at the forefront of innovation, working in a dynamic and collaborative environment that values creativity and technical excellence. With ample opportunities for professional growth and a culture that encourages bold ideas, this role offers a unique chance to make a significant impact in the rapidly evolving field of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Network Architect, GPU Fabric and AI Infrastructure in London
✨Tip Number 1
Network with industry professionals! Reach out to people in your field on LinkedIn or at networking events. We can’t stress enough how valuable personal connections are when it comes to landing a job, especially in niche areas like AI infrastructure.
✨Tip Number 2
Showcase your expertise! Prepare a portfolio or case studies of your previous GPU deployments and network architectures. We want to see your hands-on experience and how you’ve tackled challenges in real-world scenarios.
✨Tip Number 3
Practice your interview skills! Mock interviews can help you articulate your experience with InfiniBand, RoCE v2, and other technologies. We recommend getting a friend or mentor to help you refine your answers and boost your confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. We’re excited to find someone who can shape the future of our AI infrastructure, so don’t miss out on this opportunity!
We think you need these skills to ace Senior Network Architect, GPU Fabric and AI Infrastructure in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with GPU deployments and multi-vendor networks. We want to see how your background aligns with the unique challenges of AI infrastructure, so don’t hold back on those relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about building AI infrastructure and how your skills can help us tackle the challenges of network architecture at scale. Keep it engaging and personal.
Showcase Your Technical Skills:When detailing your experience, be specific about your work with InfiniBand, RoCE v2, and Ethernet fabrics. We’re looking for concrete examples that demonstrate your expertise in these areas, so don’t shy away from the technical details!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to shape the future of AI infrastructure with us!
How to prepare for a job interview at WNTD
✨Know Your Tech Inside Out
Make sure you’re well-versed in the specific technologies mentioned in the job description, like InfiniBand and RoCE v2. Brush up on your experience with GPU clusters and be ready to discuss real-world scenarios where you've tackled network issues or optimised performance.
✨Showcase Your Multi-Vendor Experience
Since the role requires multi-vendor network experience, prepare examples of how you've successfully integrated different hardware and software solutions. Be ready to explain the challenges you faced and how you overcame them, especially in high-pressure environments.
✨Understand the Bigger Picture
This isn’t just about networking; it’s about supporting AI workloads. Familiarise yourself with how network architecture impacts AI training and deployment. Be prepared to discuss how your designs can enhance performance and reliability for AI applications.
✨Prepare Questions That Matter
Think of insightful questions that show your interest in the company’s vision and the role's impact. Ask about their current challenges with GPU infrastructure or how they envision the future of AI networking. This shows you’re not just looking for a job, but are genuinely invested in their mission.
