AI Infrastructure Engineer

Responsibilities

• Lead end-to-end technical deployments for GPU neocloud and AI Factory customers
• Configure and troubleshoot bare metal GPU node infrastructure, including CNI, GPU Operator, and RDMA/InfiniBand
• Deploy and validate Kubernetes and vCluster environments
• Provide knowledge transfer to customer teams to ensure platform self-sufficiency
• Document reusable playbooks and deployment architectures
• Collaborate with Engineering and Product to surface infrastructure challenges
• Partner with Sales in the pre-sales process for deep infrastructure proof of value engagements

Requirements

• 5+ years of experience deploying and operating Kubernetes in production
• Practical knowledge of NVIDIA GPU Operators and CUDA tooling
• Deep understanding of CNI plugins, overlay networks, and load balancing
• Experience with persistent volume configuration, CSI drivers, and distributed storage (Ceph, Rook, Weka, or Longhorn)
• Ability to operate in fast-moving, ambiguous environments

Preferred Qualifications

• Automation skills with Bash, Python, or Go
• Kubernetes certifications such as CKA
• Experience writing Kubernetes Operators
• Familiarity with AI/ML inference serving and GPU scheduling
• Experience building AI automation in documentation

Benefits

• Competitive salary and equity
• Platinum-level health, dental, vision, and life insurance
• Flexible working schedule
• High workplace flexibility

About the Company

vCluster Labs is a venture-backed startup pioneering Kubernetes virtualization for the AI era. We provide the operational stack for GPU data centers, enabling AI Cloud providers and AI factories to deliver hyperscaler-like experiences.