Remote AI Infrastructure Engineer - GPU Cloud & K8s Expert

Vcluster; Singapore; Remote; SGD 155,000 - 175,000; Full time

Benefits offered by this job

Competitive Salary

Premium Insurance

Flexible Working Schedule

Workplace Flexibility

Job summary

vCluster Labs seeks an AI Infrastructure Engineer to drive production-grade Kubernetes deployments on bare metal GPU infrastructure for AI Clouds and factories. You will craft end-to-end deployment playbooks, optimize GPU nodes, and collaborate with customers and Sales in pre-sales to reach a convincing proof of value.

You will work in a remote-first, globally distributed team, with a focus on scalability, documentation, and fast feedback into product roadmaps.

Qualifications

• 5+ years deploying and operating Kubernetes in production, ideally on bare metal or high-complexity environments.
• Practical knowledge of NVIDIA GPU Operators, CUDA tooling, and systems-level configuration for GPU nodes.
• Deep understanding of CNI plugins, overlay networks, load balancing, and connectivity diagnosis in layered environments.
• Experience with persistent volumes, CSI drivers, and distributed storage (Ceph, Rook, Longhorn).
• Comfort in ambiguous, fast-moving environments and writing playbooks in real time.
• Certifications such as CKA or experience writing Kubernetes Operators.

Responsibilities

• Lead end-to-end technical deployments for GPU neocloud and AI Factory customers, from bare metal configuration to a validated vCluster environment.
• Configure and troubleshoot bare metal GPU node infrastructure, including CNI, GPU Operator, storage backends, and RDMA/InfiniBand.
• Deploy and validate Kubernetes and vCluster to provide GPU-powered managed Kubernetes.
• Work with customer teams to build self-sufficiency and operating capability.
• Document reusable playbooks and deployment architectures to accelerate future onboarding.
• Collaborate with Engineering and Product to surface infrastructure challenges and feed the roadmap.
• Join Sales in pre-sales during deep infrastructure engagements to achieve proof of value.
• Produce documentation for AI automation and knowledge sharing.

Skills

Kubernetes

GPU infrastructure

Networking

Storage & CSI

Automation (Bash/Python/Go)

CUDA tooling

Tools

NVIDIA GPU Operators

Job description

vCluster Labs seeks an AI Infrastructure Engineer to drive production-grade Kubernetes deployments on bare metal GPU infrastructure for AI Clouds and factories. You will craft end-to-end deployment playbooks, optimize GPU nodes, and collaborate with customers and Sales in pre-sales to reach a convincing proof of value.

You will work in a remote-first, globally distributed team, with a focus on scalability, documentation, and fast feedback into product roadmaps.