Senior AI Engineer / Senior Cloud AI Engineer

CYOS Solutions

8h•Hybrid

About The Position

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.

Requirements

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.
Demonstrated experience designing complex enterprise technology solutions, evaluating architectural options and implementing secure, scalable, maintainable and supportable systems.
Demonstrated expertise in at least one of the following areas: AI/ML engineering, software development, model deployment, MLOps and enterprise application integration; or Cloud infrastructure, platform engineering, systems administration, infrastructure automation, availability management and operational support.
Experience leading or contributing to complex software development, systems integration, infrastructure implementation, automated deployment or technology migration activities.
Experience selecting, implementing and improving engineering methodologies, development tools, infrastructure automation practices and technical standards to support secure and reliable technology delivery.
Demonstrated understanding of secure-by-design principles, cybersecurity requirements, technical risk management and governance obligations within enterprise technology environments.
Ability to investigate and resolve complex technical problems, identify opportunities for improvement and implement sustainable solutions that improve performance, reliability and operational effectiveness.
Strong written and verbal communication skills, with demonstrated experience presenting complex technical concepts, providing recommendations, collaborating with multidisciplinary teams and influencing stakeholders.
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, 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.
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.
Must have an active Baseline clearance.

Nice To Haves

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

Responsibilities

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.