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.
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.
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
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 …)
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