AI Cloud Engineer

M&T Resources; City of Melbourne; On-site; AUD 120,000 - 180,000; Full time

Job summary

M&T Resources in Melbourne is seeking an experienced AI Cloud Engineer to deliver scalable AI and cloud platform solutions across hybrid environments. You will build AI/ML environments, support Kubernetes workloads, and champion secure-by-design practices for government-grade systems.

Work with architects, data scientists and engineering teammates to implement IaC, CI/CD, and platform governance, enabling reliable AI services for millions of users while adhering to compliance requirements.

Qualifications

• Experience as an AI Engineer, AI Cloud Engineer, MLOps Engineer or Platform Engineer.
• Hands-on Kubernetes/OpenShift and container tech experience.
• Experience building AI/ML platforms and workloads.
• Knowledge of LLMs, Generative AI, RAG, embeddings and vector databases.
• Experience with AWS and/or Azure cloud platforms.
• Strong Python development and automation skills.
• Experience with Terraform, Ansible, GitOps, ArgoCD or similar DevOps technologies.
• Knowledge of DevSecOps, security controls and compliance requirements.
• Experience with CI/CD pipelines and modern software engineering practices.

Responsibilities

• Design and develop scalable AI and cloud platform solutions.
• Build and maintain AI/ML environments across cloud, on-premises and hybrid platforms.
• Develop and support Kubernetes-based AI workloads and infrastructure.
• Implement Infrastructure as Code (IaC) and DevOps practices.
• Collaborate with architects, cyber security specialists, data scientists and engineering teams.
• Deliver secure-by-design solutions aligned with government standards and compliance requirements.
• Support AI model deployment, monitoring, optimisation and operational management.
• Contribute to platform governance, automation and continuous improvement initiatives.

Skills

Strong experience as AI/Cloud Engineer

Kubernetes/OpenShift expertise

AI/ML platform experience

LLMs/Generative AI knowledge

Public cloud (AWS/Azure) experience

Python development

DevOps tooling (Terraform, Ansible, Ar

Tools

Kubernetes

OpenShift

Terraform

Ansible

GitOps

ArgoCD

vLLM/Azure ML (model serving)

Job description

Eligibility Applicants must be Australian Citizens and be able to obtain a Baseline Security Clearance.

Our Federal Government client is seeking an experienced AI Cloud Engineer to support the delivery of complex AI and cloud-based solutions within a large-scale technology environment.

This role offers the opportunity to work on cutting-edge AI, cloud, and platform engineering initiatives, helping establish and enhance foundational AI capabilities that support critical services delivered to millions of Australians.

Key Responsibilities

• Design and develop scalable AI and cloud platform solutions
• Build and maintain AI/ML environments across cloud, on-premises and hybrid platforms
• Develop and support Kubernetes-based AI workloads and infrastructure.
• Implement Infrastructure as Code (IaC) and DevOps practices
• Collaborate with architects, cyber security specialists, data scientists and engineering teams.
• Deliver secure-by-design solutions aligned with government standards and compliance requirements.
• Support AI model deployment, monitoring, optimisation and operational management.
• Contribute to platform governance, automation and continuous improvement initiatives.

Key Skills & Experience

• Strong experience as an AI Engineer, AI Cloud Engineer, MLOps Engineer or Platform Engineer
• Hands-on experience with Kubernetes, OpenShift and container technologies
• Experience building and supporting AI/ML platforms and workloads
• Knowledge of LLMs, Generative AI, RAG solutions, embeddings and vector databases
• Experience with AWS and/or Azure cloud platforms
• Strong Python development and automation skills
• Experience with Terraform, Ansible, GitOps, ArgoCD or similar DevOps technologies
• Knowledge of DevSecOps, security controls and compliance requirements
• Experience with CI/CD pipelines and modern software engineering practices

Desirable Experience

• Kubeflow, MLflow, SageMaker or Azure ML
• AI model serving platforms such as vLLM or TGI
• Federal Government or highly regulated environments
• AI platform engineering and cloud migration projects

If you're passionate about AI, cloud engineering and delivering enterprise-scale solutions, we'd love to hear from you.