AI Infra Engineer: GPU Kubernetes & Flexible Work

vCluster; Australia; On-site; AUD 100,000 - 150,000; Full time

Benefits offered by this job

Competitive Salary

Platinum-Level Insurance

Flexible Working Schedule

Workplace Flexibility

Job summary

vCluster is seeking an AI Infrastructure Specialist to lead GPU technical deployments and enhance customer capabilities.

In this role, you will drive Kubernetes deployments, integrate GPU infrastructures, and collaborate with customer teams to ensure independence. The position requires substantial experience with Kubernetes and GPU systems, along with an agile mindset in modern technology environments.

Flexible working conditions and a competitive compensation package are provided.

Qualifications

• 5+ years of experience deploying and operating Kubernetes in production.
• Practical knowledge of NVIDIA GPU Operators and CUDA tooling.
• Deep understanding of CNI plugins and overlay networks.
• Experience with persistent volume configuration and distributed systems.
• Comfort operating in fast-moving environments.
• Thrive in environments that reject legacy tech.

Responsibilities

• Drive end-to-end technical deployments from bare metal to validated environments.
• Configure and troubleshoot bare metal GPU node infrastructure.
• Deploy and validate Kubernetes and vCluster.
• Ensure customer teams can operate the platform independently.
• Document reusable playbooks and deployment architectures.
• Collaborate with Engineering and Product on infrastructure challenges.
• Join Sales in pre-sales processes for proof of value.

Skills

Production K8s Mastery

GPU Fluency

Networking Fundamentals

Storage Expertise

Operational Agility

Modern Tech Mindset

Tools

CUDA

Bash

Python

Go

Job description

vCluster is seeking an AI Infrastructure Specialist to lead GPU technical deployments and enhance customer capabilities.

In this role, you will drive Kubernetes deployments, integrate GPU infrastructures, and collaborate with customer teams to ensure independence. The position requires substantial experience with Kubernetes and GPU systems, along with an agile mindset in modern technology environments.

Flexible working conditions and a competitive compensation package are provided.