Head of Compute Engineering

Head of Compute Engineering

About Us

We are an early-stage neocloud purpose-built for GPU and AI workloads. Our customers are AI researchers, ML platform teams, and fast-growing AI startups who need flexible, high-performance GPU infrastructure without the complexity of hyperscalers. As we believe the future of AI will be defined by data locality, we are building a GPU compute cloud on top of our established industry-leading performance S3 storage cloud using a distributed network of colocation datacenters. We are looking for a lead Compute Engineer who can help us mature our compute products. We are a small, highly technical team looking to add deep GPU compute experience.

The Role

You will work with a small but growing team of engineers, roll up your sleeves on architecture and code, and own both the development as well as the day-to-day health of our compute infrastructure. This is the right role for a senior engineer who is ready to step fully into engineering leadership without losing their technical edge.

What You'll Do

• Contribute directly to architecture and code, particularly on GPU provisioning, orchestration, and the customer control plane

• Lead a team of engineers across platform infrastructure, backend services, and internal tooling

• Own the engineering delivery process: planning, prioritisation, and execution in close collaboration with the founding team

• Implement and maintain observability, alerting, and on-call processes to meet customer SLAs

• Hire and onboard engineers as the team grows; act as a culture carrier for technical excellence

• Work directly with early customers to understand their GPU workload requirements and feed these into the roadmap

What We're Looking For

• 7+ years of engineering experience, with at least 1-2 years in a tech lead or engineering manager capacity within the GPU space. 

• Practical experience with GPU compute - CUDA environments, NVIDIA drivers, MIG/vGPU, or similar

• Experience with container orchestration (Kubernetes, Docker) and infrastructure-as-code (Terraform, Ansible)

• Deep understanding of GPU cluster management and GPU compute layers (bare-metal provisioning, k8s, inference software, …)

• Startup mindset: you move fast, take ownership, and are energised rather than overwhelmed by ambiguity

• Bonus: 

  • Experience in  hyperscalers or Neocloud infrastructure, or data centre deployments 

  • Deep knowledge of  job schedulers (Slurm, LSF, Ray), networking  (InfiniBand/RoCE), large-scale storage systems (VAST, Weka, DAOS, Ceph, AWS S3, Lustre, GPFS), GPU inference and fine-tuning customer workloads (vLLM, LanceDB …)

Why Join

• Rare opportunity to be the technical lead at a company at the centre of the AI infrastructure boom

• Hands-on role with real technical depth - this is not a purely managerial position

• Attractive equity for an early employee in a high-growth space

• Work directly with founders and have a real voice in product and company direction