Senior AI Platform Engineer

Talent; Canberra; Hybrid; AUD 120,000 - 190,000; Part time

Job summary

Talent seeks a Cloud AI Engineer to design and maintain scalable AI-focused cloud infra across on-prem, cloud, and hybrid environments. You will lead deployments, optimize AI platforms and implement robust IaC and DevOps practices to support enterprise AI workloads.

The role requires hands-on AWS/Azure experience, deep Kubernetes/OpenShift expertise, and strong Python/Linux scripting capabilities. Collaboration with data scientists and security teams is essential for reliable, secure AI

Qualifications

• Hands-on Cloud AI Engineering experience designing, implementing and supporting enterprise AI/ML environments.
• Strong experience with AWS and/or Azure services, including SageMaker or Azure AI/ML.
• Expertise in Kubernetes and OpenShift, including deployment, security and ops management.
• Proficient in IaC and DevOps tooling (Terraform, Ansible, GitLab, GitHub Actions, Azure DevOps or Argo CD).
• Proficiency in Python, Linux, scripting, networking and automation for cloud infra.
• Practical exposure to AI/ML platforms, including MLOps, model serving and monitoring.
• Solid cloud security, governance, performance, availability and stakeholder engagement.

Responsibilities

• Design, build and maintain secure, scalable cloud infrastructure supporting AI workloads.
• Lead deployment and optimization of AI platforms across on-prem, public cloud and hybrid environments.
• Develop reusable infrastructure solutions using IaC, automation and modern DevOps practices.
• Implement and manage container-based AI environments using Kubernetes, OpenShift and related tech.
• Collaborate with architects, data scientists and cybersecurity teams to deliver enterprise AI solutions.
• Establish monitoring, performance optimization, security controls and standards for AI infra.
• Provide technical leadership and resolve complex infrastructure challenges.

Skills

Cloud AI Engineering

AWS/Azure

Kubernetes/OpenShift

Infrastructure as Code

Python/Linux

AI/ML platforms

Security governance

Tools

Terraform

Ansible

GitLab/GitHub Actions

Azure DevOps/Argo CD

Docker

Job description

• Contract: Up to 12 months, with potential extension opportunities.
• Location: Canberra, Sydney, Melbourne, Brisbane, Adelaide or Perth. Initial two weeks onsite, followed by negotiated hybrid arrangements.
• Security Clearance: Must hold a Baseline security clearance.
• Key Technologies: AWS, Azure, Kubernetes, OpenShift AI, Python, Terraform, DevOps, AI/ML and Generative AI platforms.

Your Duties Will Include

• Design, build and maintain secure, scalable cloud infrastructure supporting AI, Machine Learning and Generative AI workloads.
• Lead the deployment, integration and optimisation of AI platforms across on-premises, public cloud and hybrid environments.
• Develop reusable infrastructure solutions using Infrastructure as Code, automation and modern DevOps practices.
• Implement and manage container-based AI environments using Kubernetes, OpenShift and associated platform technologies.
• Collaborate with architects, data scientists, cybersecurity specialists and engineering teams to deliver reliable enterprise AI solutions.
• Establish monitoring, performance optimisation, security controls and operational standards for AI infrastructure.
• Provide technical leadership, resolve complex infrastructure challenges and contribute to architecture decisions and continuous improvement.

Skills And Experience We Are Looking For

• Demonstrated hands-on Cloud AI Engineering experience, including designing, implementing and supporting enterprise AI/ML environments.
• Strong experience with AWS and/or Microsoft Azure, ideally including services such as Amazon SageMaker or Azure AI/ML.
• Demonstrated expertise in Kubernetes, OpenShift/OpenShift AI, Docker and container orchestration, including deployment, security and operational management.
• Strong capability in Infrastructure as Code and DevOps, using technologies such as Terraform, Ansible, GitLab, GitHub Actions, Azure DevOps or Argo CD.
• Proficiency in Python, Linux administration, scripting, networking and automation to support complex cloud infrastructure.
• Practical experience supporting AI/ML and Generative AI platforms, including model deployment, MLOps, Large Language Models, model serving and monitoring. Exposure to GPU infrastructure, Hugging Face, vector databases or Retrieval-Augmented Generation would be advantageous.
• Strong understanding of cloud security, governance, performance, availability and capacity management, combined with excellent stakeholder engagement and technical problem-solving skills.