Senior Cloud AI Engineer

Key Requirements

• Australian Citizen — you must be eligible to obtain and maintain a Baseline security clearance before commencing.
• 5+ years hands-on Cloud AI Engineering — greenfield and brownfield AI/ML environments across on-prem, public cloud and hybrid platforms; this is a senior EL1-equivalent gig, so bring the receipts.
• Based in Melbourne, VIC or Sydney, NSW — hybrid role; you must be within reasonable commute distance of the office and ready to be onsite for the first two weeks.

The GigG'day, Cloud AI trailblazers!

If you live and breathe AI/ML platforms, love building secure-by-design cloud infrastructure, and want your work to genuinely improve the lives of millions of Australians — read on.

Picture this…

You're embedded in a large-scale Technology and Digital Program at a Federal Agency, working hybrid from Melbourne, VIC or Sydney, NSW. Your first fortnight is onsite getting your bearings, then you settle into a flexible hybrid rhythm. You're the go-to Cloud AI Engineer — designing, deploying and optimising AI/ML workloads across on-prem and public cloud platforms, collaborating daily with Data Scientists, Cyber Security specialists, and Architecture teams to build foundational platform capability that scales.

This is an up-to-12-month contract (with extensions up to 24 months) at an EL1-equivalent seniority level. The work is complex, the autonomy is real, and the impact on government service delivery is tangible.

What you'll be doing

• Designing and maintaining secure, scalable cloud infrastructure for AI, ML and Generative AI services
• Leading enterprise AI solution implementation — performance, resilience, operational excellence
• Driving DevSecOps and secure-by-design principles across AI platforms
• Wrangling Kubernetes, OpenShift AI, LLMs, MLOps pipelines, GPU engineering and IaC tooling
• Acting as the technical anchor across complex, multi-team delivery programmes
• Mentoring APS teams and sharing your expertise as the resident SME

We know because we do

At Cloud Delivered, we're senior ICT contractors ourselves. We know what a genuinely meaty Cloud AI Engineering gig looks like — and this one is the real deal. The tech stack is cutting-edge, the mission matters, and the team is serious about delivery.

If you tick the essentials below, we'll help you put your best foot forward and nail this one.

Talk to us:

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

Essential CriteriaEssential Criteria (SFIA-aligned)1. Availability Management — Level 5 (SFIA)

Advises on service availability planning, design and improvement; investigates availability breaches and initiates remedial action; develops disaster recovery plans and manages their testing.

2. Capacity Management — Level 4 (SFIA)

Monitors service component capacity and acts on shortfalls; controls demand on resources; contributes to capacity modelling, planning and design.

3. IT Infrastructure — Level 4 (SFIA)

Provides technical expertise for operational procedures; implements agreed infrastructure changes and maintenance; uses tools for load and performance statistics; scripts automated provisioning, testing and deployment; resolves operational issues and proposes improvements.

4. Problem Management — Level 4 (SFIA)

Initiates and monitors actions to investigate and resolve problems; determines fixes; implements agreed remedies and preventative measures; supports analysis of patterns and trends.

5. Programming/Software Development — Level 3 (SFIA)

Designs, codes, verifies, tests, documents, amends and refactors moderately complex programs/scripts to agreed standards; reports progress; proposes solutions to issues; collaborates in reviews.

6. Systems Design — Level 5 (SFIA)

Designs large or complex systems, with impact analysis of options and trade-offs; balances functional and non-functional requirements; reviews designs; manages risks; contributes to design policies, standards and selection of architecture components.

7. Systems Installation and Removal — Level 5 (SFIA)

Takes responsibility for installation and decommissioning projects; leads the team and customer information flow; develops quality plans and method statements; monitors installation effectiveness and recommends change.

Desirable CriteriaDesirable Knowledge, Qualifications or Experience

• Strong communication and negotiation skills; professional presentation skills.
• Kubernetes, OpenShift and OpenShift AI: namespaces, RBAC, operators, CRDs, ingress/routes, secrets, workbenches, AI Pipelines/Kubeflow, model registry and serving, distributed workloads, monitoring.
• Containers and platform engineering: Docker/Podman, image creation, registries, scanning, vulnerability management, container security, secure software supply chain.
• Linux administration, networking and storage: DNS, TLS, proxies, load balancing, firewalls, certificates, scripting, on-premise to cloud connectivity.
• DevOps, CI/CD and IaC: Git, GitLab/GitHub/Azure DevOps, Tekton, GitOps/Argo CD, Terraform and/or Ansible, automated build, test and deployment pipelines.
• Python and scripting for automation, AI/ML integration, APIs, platform tooling and operational support.
• AI/ML engineering and MLOps: model lifecycle, training, inference, evaluation, deployment, monitoring, optimisation, automated build-and-release.
• LLM and Generative AI tooling: vLLM/TGI or equivalent, Hugging Face, LLM APIs, embeddings, RAG, vector databases, prompt/evaluation tooling, AI agents, foundation models.
• GPU engineering: NVIDIA GPUs, CUDA fundamentals, scheduling, resource allocation, utilisation and troubleshooting.
• APIs and enterprise integration: REST, OAuth/OIDC, API gateways, streaming platforms, data lakes, feature stores.
• Cloud platforms and AI services: at least one of AWS or Azure (preferably two), with exposure to SageMaker or Azure AI/ML.
• Object storage and data management, including S3-compatible storage for OpenShift AI pipelines, models and datasets.
• Observability: Prometheus/Grafana, logs, metrics, tracing, model/application monitoring.
• Security, governance and compliance: RBAC, secrets, certificates, network policies, vulnerability scanning, DevSecOps, data sovereignty, security classifications, privacy, Australian Government regulatory requirements.
• FinOps: cost transparency, usage optimisation and financial governance for cloud and AI workloads.
• Applying architecture principles and enterprise technologies to turn complex requirements into scalable, supportable solutions.
• Proven ability to explain complex technical concepts, facilitate stakeholder discussions and drive consensus on project and organisational goals.

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 at the Melbourne or Sydney office when required?
• (Expected answer: yes / no)
• Are you located in VIC or NSW or will you relocate?
• (Expected answer: yes / no)
• Are you an Australian Citizen eligible to obtain and maintain a Baseline security clearance?
• (Expected answer: yes / no)
• How many years of total experience have you worked in Federal Government ICT roles?
• (Expected answer: a number)
• How many years of hands-on experience do you have as a Cloud AI Engineer, including solution design, implementation and operation of greenfield and brownfield AI/ML environments?
• (Expected answer: a number)
• How many years of experience do you have with availability management at SFIA Level 5, including disaster recovery planning and testing?
• (Expected answer: a number)
• How many years of experience do you have with IT infrastructure management, including IaC scripting for provisioning, testing and deployment?
• (Expected answer: a number)
• How many years of experience do you have with systems design at SFIA Level 5, including large or complex system design and trade-off analysis?
• (Expected answer: a number)
• How many years of experience do you have with AI/ML engineering and MLOps, including model lifecycle management, training, inference, deployment and monitoring?
• (Expected answer: a number)
• How many years of experience do you have with Kubernetes and/or OpenShift AI, including namespaces, RBAC, operators and AI Pipelines/Kubeflow?
• (Expected answer: a number)
• How many years of experience do you have with DevOps, CI/CD and Infrastructure as Code tooling (e.g. Terraform, Ansible, GitOps/Argo CD)?
• (Expected answer: a number)
• How many years of experience do you have with LLM and Generative AI tooling, including Retrieval-Augmented Generation, vector databases and foundation models?
• (Expected answer: a number)
• How many years of experience do you have with security, governance and compliance in cloud environments, including DevSecOps 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 and GPU scheduling?
• (Expected answer: a number)
• On a scale of 1 to 10, how would you rate your ability to articulate complex technical concepts clearly and drive consensus with senior stakeholders?
• (Expected answer: a rating)