AI Infrastructure Engineer
vCluster Labs · Remote · Remote · EMEA · United States ·
COMPENSATION
€90k – €105k
Listed on the employer's job board (Ashby)
- Fully remote
- Kubernetes + GPU
- Pre-sales technical role
- Bare metal infrastructure
- Senior level
You will work directly with neoclouds and AI factories to transform bare metal GPU nodes into production-ready managed Kubernetes environments. Operating in a pre-sales proof of value context, you will configure infrastructure, validate deployments, and create reusable playbooks that scale customer onboarding.
This position requires deep technical engagement with customers to ensure self-sufficiency while feeding field insights back to the engineering and product teams. You will help organizations offer Kubernetes as a managed service on their own hardware rapidly.
What you'll do
- Drive end-to-end technical deployments from bare metal setup to validated vCluster environments
- Configure and troubleshoot GPU node infrastructure including CNI, GPU Operator, and RDMA
- Deploy and validate Kubernetes clusters to provide GPU-powered managed services
- Collaborate with customer teams to build operational self-sufficiency and knowledge transfer
- Document reusable playbooks and deployment architectures for future customer engagements
- Partner with Sales during pre-sales processes to achieve meaningful proofs of value
- Provide feedback to Engineering and Product on recurring infrastructure challenges
What you'll need
- 5+ years of experience deploying and operating Kubernetes in production environments
- Practical knowledge of NVIDIA GPU Operators, CUDA tooling, and systems-level configuration
- Deep understanding of CNI plugins, overlay networks, and connectivity diagnosis
- Experience with persistent volume configuration, CSI drivers, and distributed storage systems
- Comfort working in ambiguous, fast-moving environments requiring real-time problem solving
- Preference for modern technology stacks over legacy systems
Nice to have
- Scripting automation skills using Bash, Python, or Go
- Certified Kubernetes Administrator (CKA) certification or Operator development experience
- Familiarity with inference serving, GPU scheduling, and LLM deployment tooling
- Experience building documentation to contribute to shared knowledge bases
Stack
- Kubernetes
- vCluster
- NVIDIA GPU Operator
- CUDA
- CNI
- RDMA
- InfiniBand
- Ceph
- Rook
- Weka
- Longhorn
- Bash
- Python
- Go
How you'll work
- Fully remote with a distributed global team
- Flexible working schedule focused on results rather than fixed hours
- Headquarters in San Francisco but open to global locations
What you get
- Competitive compensation package including equity
- Premium health, dental, vision, and life insurance
- Insurance plans covering eligible dependents
- Flexible work environment adaptable to life changes