Senior AI Engineer / Senior Cloud AI Engineer

Application closing date: Thursday, 22 October 2026 • 11:59pm, Canberra time

Estimated start date: Monday, 16 November 2026

Location of work: VIC

Working arrangements: Full-time onsite for the first 2 weeks. A hybrid WFH arrangement, usually a minimum of 2 days per week onsite, will be considered from the location of their capital city.

Length of contract: 12 months

Contract extensions: Up to a maximum of 24 months

Security clearance: Must have an active Baseline clearance

Rates: $110 - $140 per hour (inc. super)

Services Australia is at the frontline of government service delivery, supporting millions of Australians, and is central to a vision of becoming a world leader in government service delivery. The agency is using cutting-edge technology to build world-class platforms and capabilities that help Australians access essential services.

Services Australia is seeking experienced Senior AI Engineers and Senior Cloud AI Engineers to support the design, development, implementation and optimisation of enterprise Artificial Intelligence (AI), Machine Learning (ML) and cloud-native technology solutions across the Technology and Digital Program (TDP) Group.

These opportunities suit senior technical professionals with expertise in AI software engineering, cloud infrastructure, platform engineering, DevOps, MLOps, solution architecture or enterprise systems integration.

Successful candidates will specialise in either AI software development and engineering or cloud infrastructure and AI platform engineering, contributing to the delivery of secure, scalable and highly available enterprise AI capabilities.

The roles involve working across on-premises, public cloud and hybrid environments, including greenfield implementations and the enhancement, integration and migration of existing technology platforms.

Candidates will collaborate with Data Scientists, Solution Architects, Cyber Security, Infrastructure and Core Data teams to establish foundational AI capabilities, develop reusable engineering patterns, enforce governance and implement secure-by-design solutions aligned with Australian Government frameworks and regulations.

The successful candidates will operate with a high degree of autonomy, providing technical leadership, specialist advice and guidance across complex technology initiatives. They will be expected to identify opportunities for innovation, resolve complex technical challenges, influence stakeholders and contribute to the strategic direction of enterprise technology solutions.

Applicants with a strong background in either AI software engineering or cloud/platform infrastructure engineering are encouraged to apply. Experience across both disciplines is highly regarded but is not mandatory.

Key duties and responsibilities:
Depending on the candidate's technical specialisation, responsibilities may include:

• Design, develop, implement and optimise enterprise AI, ML and Generative AI platforms, applications and supporting infrastructure.
• Lead the delivery of secure, scalable and reusable engineering solutions across public cloud, on-premises and hybrid environments.
• Design and implement cloud-native architectures, infrastructure automation and enterprise AI engineering frameworks.
• Develop, integrate and maintain AI/ML solutions, including model deployment, inference, evaluation, monitoring and lifecycle management.
• Design and support highly available cloud infrastructure, including resource allocation, capacity planning, resilience and operational performance.
• Lead complex software development, systems integration, platform deployment, migration and technical implementation activities.
• Develop and maintain Infrastructure as Code (IaC), CI/CD pipelines, automated deployments and secure software delivery processes.
• Apply DevSecOps, secure-by-design principles and Australian Government security, privacy and governance requirements.
• Analyse technical requirements, evaluate solution options and recommend appropriate architecture, technologies and implementation approaches.
• Identify, investigate and resolve complex technical issues affecting applications, platforms, infrastructure and enterprise services.
• Provide technical leadership, specialist advice and guidance to multidisciplinary delivery teams.
• Establish engineering standards, reusable architecture patterns, technical documentation and operational procedures.
• Collaborate with internal and external stakeholders to ensure solutions align with business requirements and organisational objectives.
• Drive innovation, continuous improvement, technical governance and adoption of emerging technologies.
• Support operational readiness, system reliability, release management, knowledge transfer and ongoing service improvement.

Technical skills required but not limited to:
Candidates should demonstrate strong experience in one or more of the following technical areas. The specific requirements will depend on the position and technical specialisation.

AI Engineering, Software Development and MLOps:

• Experience designing, developing and implementing enterprise AI/ML solutions, including greenfield and brownfield environments.
• Strong programming and software engineering skills, particularly Python, automation, APIs and enterprise application integration.
• Experience with AI/ML engineering and MLOps, including model development, training, inference, evaluation, deployment, monitoring and lifecycle management.
• Experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), embeddings, vector databases, AI agents and foundation models.
• Experience with AI frameworks and tooling such as Hugging Face, vLLM/TGI, Kubeflow, AWS SageMaker, Azure AI or Azure Machine Learning.
• Experience in software architecture, systems design, integration, configuration management, release management and automated testing.
• Ability to provide technical leadership across complex software development and AI engineering initiatives.

Cloud Infrastructure, Platform Engineering and DevOps:

• Experience designing, implementing and supporting enterprise cloud infrastructure across AWS, Microsoft Azure, on-premises or hybrid environments.
• Experience with Kubernetes, OpenShift, OpenShift AI or equivalent container orchestration and cloud-native platforms.
• Experience with Docker/Podman, container image management, registries, vulnerability scanning and secure software supply chain practices.
• Experience with Infrastructure as Code and automation technologies such as Terraform, Ansible, GitOps, Argo CD, GitLab, GitHub Actions or Azure DevOps.
• Experience with Linux administration, networking, storage, DNS, TLS, load balancing, ingress, certificates and connectivity between cloud and on-premises environments.
• Experience with cloud infrastructure availability, capacity planning, performance optimisation, disaster recovery and operational resilience.
• Experience with infrastructure monitoring and observability, including Prometheus, Grafana, AWS CloudWatch, Azure Application Insights or equivalent technologies.
• Experience with enterprise platform deployment, migration, systems installation, infrastructure troubleshooting and problem management.
• Experience applying FinOps principles, including cloud cost transparency, resource optimisation and financial governance.

Cloud Infrastructure, Platform Engineering and DevOps:

• NVIDIA GPU infrastructure, CUDA fundamentals, GPU scheduling and AI workload optimisation.
• OpenShift AI pipelines, model registries, model serving and S3-compatible object storage.
• Enterprise integration technologies, including REST APIs, OAuth/OIDC, API gateways, streaming platforms and data lakes.
• DevSecOps, RBAC, secrets management, network security, vulnerability management and secure platform configuration.
• Australian Government security frameworks, privacy obligations, data sovereignty and regulatory compliance.
• Experience delivering enterprise AI platforms or cloud-native solutions within government or other highly regulated environments.

Essential criteria
Applicants will be assessed against the criteria relevant to their technical specialisation. Candidates are not required to demonstrate every capability listed across both specialisations.

1. Senior Technical Leadership and Specialist Advice
   Demonstrated experience providing technical leadership, specialist advice and guidance across complex software engineering, AI/ML or cloud infrastructure initiatives. Ability to work autonomously, resolve complex technical challenges and influence technical decisions.
2. Solution Architecture and Systems Design
   Demonstrated experience designing complex enterprise technology solutions, evaluating architectural options and implementing secure, scalable, maintainable and supportable systems.
3. AI Engineering or Cloud Infrastructure Expertise
   Demonstrated expertise in at least one of the following areas:
   1. AI/ML engineering, software development, model deployment, MLOps and enterprise application integration; or
   2. Cloud infrastructure, platform engineering, systems administration, infrastructure automation, availability management and operational support.
4. Development, Deployment and Systems Integration
   Experience leading or contributing to complex software development, systems integration, infrastructure implementation, automated deployment or technology migration activities.
5. Engineering Methods, Tools and Standards
   Experience selecting, implementing and improving engineering methodologies, development tools, infrastructure automation practices and technical standards to support secure and reliable technology delivery.
6. Security, Governance and Compliance
   Demonstrated understanding of secure-by-design principles, cybersecurity requirements, technical risk management and governance obligations within enterprise technology environments.
7. Problem Solving and Continuous Improvement
   Ability to investigate and resolve complex technical problems, identify opportunities for improvement and implement sustainable solutions that improve performance, reliability and operational effectiveness.
8. Communication and Stakeholder Engagement
   Strong written and verbal communication skills, with demonstrated experience presenting complex technical concepts, providing recommendations, collaborating with multidisciplinary teams and influencing stakeholders.

Desirable criteria

1. Experience delivering AI/ML, Generative AI or cloud-native infrastructure solutions within Australian Government environments.
2. Experience with both AI software engineering and cloud/platform infrastructure engineering.
3. Experience with emerging AI technologies, model serving, GPU infrastructure and enterprise AI platform operations.
4. Experience leading technical teams, developing engineering standards and providing mentoring or knowledge transfer.
5. Experience working within Agile, DevOps, ITIL or other structured technology delivery frameworks.

HOW TO APPLY

Please provide an updated CV (preferably 3–5 pages) demonstrating your suitability for the role based on your technical experience and specialisation.

Applicants should clearly outline their experience in AI software engineering, cloud infrastructure/platform engineering, or both, including examples of relevant projects, technical responsibilities and leadership experience.

Shortlisted candidates will be required to provide a one-page pitch of no more than 5,000 characters addressing the selection criteria relevant to the specific opportunity.

Applications will be assessed based on demonstrated technical capabilities, relevant experience, leadership skills and suitability for the available positions.