Head of Compute Engineering
Quick Summary
We have built a cloud object storage similar to AWS S3, now optimised for AI and compute. Our market success has already been proved by our commercial hyper-growth,
We have built a cloud object storage similar to AWS S3, now optimised for AI and compute. Our market success has already been proved by our commercial hyper-growth, based on our channel-based GTM strategy. While we build a high performance compute platform and a comprehensive suite of cloud services, we are redefining the cloud ecosystem by bridging the gap between decentralized infrastructure (DePIN), mainstream B2B cloud use cases, and most recently AI Applications — all from our HQ in Hamburg.
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.
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Contribute directly to architecture and code, particularly on GPU provisioning, orchestration, and the customer control plane
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Lead a team of engineers across platform infrastructure, backend services, and internal tooling
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Own the engineering delivery process: planning, prioritisation, and execution in close collaboration with the founding team
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Implement and maintain observability, alerting, and on-call processes to meet customer SLAs
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Hire and onboard engineers as the team grows; act as a culture carrier for technical excellence
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Work directly with early customers to understand their GPU workload requirements and feed these into the roadmap
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7+ years of engineering experience, with at least 1-2 years in a tech lead or engineering manager capacity within the GPU space.
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Practical experience with GPU compute - CUDA environments, NVIDIA drivers, MIG/vGPU, or similar
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Experience with container orchestration (Kubernetes, Docker) and infrastructure-as-code (Terraform, Ansible)
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Deep understanding of GPU cluster management and GPU compute layers (bare-metal provisioning, k8s, inference software, …)
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Startup mindset: you move fast, take ownership, and are energised rather than overwhelmed by ambiguity
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Bonus:
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Experience in hyperscalers or Neocloud infrastructure, or data centre deployments
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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 …)
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Listing Details
- Posted
- March 20, 2026
- First seen
- March 26, 2026
- Last seen
- April 24, 2026
Posting Health
- Days active
- 29
- Repost count
- 0
- Trust Level
- 32%
- Scored at
- April 24, 2026
Signal breakdown
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