Lead Compute Engineer managing and developing GPU compute products at a neocloud AI infrastructure startup. Collaborating with engineers and customers to enhance performance and scalability.
Responsibilities
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
Requirements
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 …)
Benefits
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
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