Key Requirements

- You must be an Australian Citizen — this is a federal government role and no visa holders (including PR) will be considered.
- You must be eligible to obtain a Baseline security clearance.
- You need 5+ years of hands-on AI/ML engineering experience spanning greenfield and brownfield on-premises, public cloud and hybrid platforms — this is a senior technical gig, not a stepping-stone role.

The GigG'day, trailblazers!

Cloud Delivered is on the hunt for a sharp AI Engineer to join a high-impact federal agency team delivering next-generation AI platforms. This is the kind of gig where your work genuinely matters.

Picture this: You're embedded in a cooperative crew of Data Scientists, Architects, Cyber Security pros and Core Data engineers, building and operating on-premises AI/ML platforms from the ground up — greenfield builds, brownfield enhancements, the lot. You'll be deploying secure-by-design architectures, wrangling Kubernetes and OpenShift AI, shipping LLM and Generative AI workloads, and keeping GPU-accelerated inference humming along. The role is hybrid — you'll need to be onsite for the first two weeks to get your bearings, then settle into a rhythm of at least 2–3 days in the office per week.

We know because we do — we've been contractors ourselves, and we know what separates a genuinely strong AI Engineer from someone who's just ticked the buzzword boxes. We're looking for someone who can own the full AI/ML lifecycle: model training, inference, MLOps, RAG pipelines, GPU scheduling, DevSecOps, IaC — the whole stack. If you can articulate complex technical concepts to non-technical stakeholders and drive consensus, you'll fit right in.

The contract runs up to 12 months with potential for extension, and it's sitting at an APS6-equivalent experience level. You'll need to be an Australian Citizen eligible for Baseline clearance.

If you tick the essentials below, we'll help you nail this one.

Talk to us:

- Cloud Delivered
- Tristan Coleman
- Dan Harrison
- Ursan Sachdeva

Essential Criteria
1. AI and Machine Learning Engineering — SFIA MLNG Level 4: Works independently on defined AI/ML engineering activities, selecting appropriate techniques and applying established organisational standards and practices.
2. AI Platform and Systems Integration — SFIA SINT Level 4: Integrates systems and services using established patterns and technologies and resolves integration problems within a defined technical environment.
3. Data Engineering — SFIA DENG Level 4:



Designs and develops data processing components and pipelines and applies established data engineering practices to defined business requirements.
4. Information Security — SFIA SCTY Level 3: Applies established security practices and organisational controls to development and operational activities.
5. Programming/software development SFIA PROG Level 5: Develops software from specifications and contributes to technical design, implementation, testing and maintenance of software components.
6. Deployment of software – SFIA DEPL Level 4: Plans and executes deployments of complex software releases, manages continuous deployment using automation tools, optimises deployment process for efficiency and performance. Software lifecycle engineering – SFIA SLEN Level 4: Elicits requirements for systems and software lifecycle working practices and automation, designs options for the working environment of methods, procedures, techniques and people and selects systems and software lifecycle working practices for software components and microservices. Deploys automation to achieved well-engineered, secure outcomes.

Desirable Criteria
1. Specialist advice SFIA TECH Level 4: Provides detailed and specific advice to support the organisation's planning and operations, typically related to the immediate area of responsibility, recognises boundaries of specialist knowledge and appropriately collaborates with other specialists to ensure advice given is professionally sound.
2. Systems design SFIA DESN Level 4: Designs system components using appropriate modelling techniques following agreed architectures, design standards, patterns and methodology, evaluates alternative design options and trade-offs, models / prototypes behaviour of proposed system components to enable approvals by stakeholders and verifies and improves own design against specifications.
3. Data Analytics SFIA DAAN Level 4: Conducts end-to-end data analysis, defining data requirements and ensuring data integrity, applies advanced analytical and statistical techniques to extract meaningful insights and develop predictive models, communicates complex findings to stakeholders and contributes to data analytics processes and standards.

Screening Questions YOU WILL BE ASKED:Seriously,



don't bother if you don't think you'll pass these questions.

- Are you an Australian Citizen?
- (Expected answer: yes / no)
- What is the highest active or dormant security clearance you currently hold?
- (Expected answer: one of the listed options)
- Can you attend onsite in Melbourne?
- (Expected answer: yes / no)
- Do you live in Victoria or are you willing to relocate?
- (Expected answer: yes / no)
- Are you an Australian Citizen? (This is a federal government role — PR and visa holders cannot be considered.)
- (Expected answer: yes / no)
- Are you eligible to obtain a Baseline security clearance?
- (Expected answer: yes / no)
- How many total years have you worked in federal government ICT delivery?
- (Expected answer: a number)
- How many years of hands-on experience do you have as an AI Engineer, including solution design, implementation and operation of greenfield and brownfield AI/ML environments across on-premises, public cloud and hybrid platforms?
- (Expected answer: a number)
- How many years of experience do you have with Kubernetes, OpenShift and OpenShift AI (including namespaces, RBAC, operators, CRDs, AI Pipelines/Kubeflow, model serving and distributed workloads)?
- (Expected answer: a number)
- How many years of experience do you have in AI/ML engineering and MLOps, including model lifecycle management, training, inference, evaluation, deployment, monitoring and automated model build-and-release processes?
- (Expected answer: a number)
- How many years of experience do you have with LLM and Generative AI tooling, including vLLM/TGI or equivalent, Hugging Face, Retrieval-Augmented Generation, vector databases and AI agents?
- (Expected answer: a number)
- How many years of experience do you have in DevOps, CI/CD and Infrastructure as Code, including Git, GitOps/Argo CD, Terraform and/or Ansible, and automated build, test and deployment pipelines?
- (Expected answer: a number)
- How many years of experience do you have in security, governance and compliance, including DevSecOps, data sovereignty, security classifications, privacy obligations and Australian Government regulatory requirements?
- (Expected answer: a number)
- How many years of experience do you have with GPU engineering, including NVIDIA GPUs, CUDA fundamentals, GPU scheduling and resource allocation?
- (Expected answer: a number)
- How many years of experience do you have in Data Analytics (SFIA DAAN), including end-to-end data analysis, advanced analytical and statistical techniques, and communicating findings to stakeholders?
- (Expected answer: a number)

📌 AI Engineer (Melbourne)
🏢 Cloud Delivered
📍 Melbourne