AI Infrastructure Engineer

This is a fully remote position, open to applicants in Singapore.

📋 Description

• Oversee comprehensive technical implementations for GPU neocloud and AI Factory clients, encompassing bare metal setup to validated vCluster environments.

• Set up and troubleshoot bare metal GPU node infrastructure, which includes CNI, GPU Operator, distributed storage backends, and RDMA/InfiniBand.

• Implement and verify Kubernetes and vCluster for GPU-driven managed Kubernetes.

• Collaborate with client teams to foster operational self-sufficiency.

• Create documentation for reusable playbooks and deployment architectures.

• Work in conjunction with Engineering and Product teams to highlight infrastructure issues and guide the roadmap.

• Assist Sales in pre-sales proof-of-value initiatives that demand in-depth infrastructure knowledge.

⛳️ Requirements

• A minimum of 5 years of experience in deploying and managing Kubernetes in a production setting.

• Hands-on knowledge of NVIDIA GPU Operators, CUDA tools, and systems-level configuration for GPU nodes.

• Profound understanding of CNI plugins, overlay networks, load balancing, and connectivity diagnostics within layered environments.

• Experience with persistent volume configurations, CSI drivers, and distributed systems such as Ceph, Rook, Weka, or Longhorn.

• Ability to operate effectively in fast-paced and ambiguous environments.

• Familiarity with automation scripting in Bash, Python, or Go is a plus.

• CKA certification or experience in developing Kubernetes Operators is an advantage.

• Experience with inference serving, GPU scheduling, and tools for deploying LLMs is a bonus.

• Background in creating AI automation documentation is an additional benefit.

🏝️ Benefits

• Equity

• Bonus

• Health insurance

• Dental insurance

• Vision insurance

• Life insurance

• Plans available for eligible dependents

• Flexible working schedule

• Workplace flexibility

• Remote-first culture