About Hivenet

We're building the future of cloud infrastructure. Hivenet is a distributed cloud platform offering GPU computing for AI/ML workloads, secure file storage, and fast file transfer—all powered by a sustainable, decentralized architecture that reduces carbon footprint by 77% compared to traditional data centers. We're a well-funded, remote-first team scaling fast across EMEA.

About the Team

The Compute GPU team owns our core GPU cloud infrastructure: Platform Services, billing, and the foundational components that power Hivenet Compute. We serve high-performance GPU instances across multiple regions to AI researchers and enterprises.

What You'll Do

• Design and build Kubernetes operators and controllers for GPU instance management
• Develop Platform Services APIs using NestJS and Golang
• Implement billing and usage tracking systems for GPU compute resources
• Contribute to our GitOps pipeline with FluxCD and improve deployment reliability
• Collaborate on system architecture decisions and participate in code reviews

What You Bring

• 4+ years of backend engineering experience with production systems
• Strong Kubernetes experience: operators, CRDs, controllers, or cluster administration
• Proficiency in Golang and/or TypeScript/NestJS
• Experience with distributed systems and cloud-native architecture
• Proficiency with AI-assisted development tools and agentic coding workflows
• Demonstrated ability to use AI coding assistants effectively—rapidly prototyping, debugging, and refactoring while maintaining strong engineering judgment and production standards

Bonus Points

• Experience with GPU infrastructure, CUDA/ROCm drivers, or ML serving frameworks
• Familiarity with KubeVirt, KVM, or virtualization
• Background with FluxCD, ArgoCD, or GitOps patterns

The Reality

• This is an early-stage startup—you'll wear many hats
• We move fast and expect ownership mentality
• You'll be building processes, not following existing ones

What We Offer

• Full remote work from anywhere (EMEA timezone preferred)
• Equipment budget to set up your ideal workspace
• Company offsites to connect with the team
• Career growth in a scaling engineering organization
• Work on cutting-edge distributed systems and AI infrastructure