1 day ago

Cloud & AI Platform Specialist - Azure

Datacom

Melbourne

1 day ago

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Datacom is seeking a Cloud & AI Platform Specialist - Azure to help customers design, build, and improve secure Azure cloud and AI platforms. The role combines strategic consulting with hands-on platform engineering, covering discovery, architecture, implementation, and operations. Requires strong Azure consulting experience, Infrastructure as Code skills, and practical knowledge of AI services and modern delivery practices.

AI-enabledOn-siteFull-timeEntry LevelAzureTerraform

Cloud & AI Platform Specialist - Azure

Apply

AI-enabledOn-siteFull-timeEntry LevelAzure

Salary

Not specified

Work Location

Melbourne, Victoria, Australia, AU

Work Model

On-site

Employment Type

Full-time

Experience Level

Not Applicable

Core Qualifications

Technical (Must-have)

AzureTerraformBicepInfrastructure as CodeGitOpsCI/CDAzure AI FoundryAzure OpenAIAzure AI SearchRetrieval-Augmented GenerationVector SearchResponsible AIGitHub EnterpriseGitHub ActionsGitHub Advanced SecurityGitHub CopilotPythonTypeScriptC#JavaGoRustKubernetesAPIsContainersTest AutomationSecure Software Development

Soft Skills

CommunicationStakeholder EngagementCommercial AwarenessMentoring

Preferred Qualifications

Technical (Nice-to-have)

AI GatewaysModel ObservabilityModel Context ProtocolFinOpsAdvanced Security ArchitectureProduct DevelopmentSoftware-as-a-ServiceManaged Service TransitionMentoring

Key Responsibilities

•Lead Azure discovery, advisory and architecture engagements, translating customer objectives into secure and practical platform designs.
•Design and implement Azure platform foundations, including landing zones, identity, networking, governance, policy, security controls and self-service capabilities.
•Build repeatable automation using Infrastructure as Code, GitOps, policy as code and continuous integration and delivery practices.
•Design and deploy AI-ready environments using services such as Azure AI Foundry, Azure OpenAI and Azure AI Search, including retrieval-augmented generation, vector search and secure data integration patterns.
•Develop and support governed agentic workflows, including tool integrations, human oversight, lifecycle controls, testing, monitoring and cost management.
•Establish responsible AI practices, including model and agent governance, data and prompt controls, security guardrails, consumption management and operational accountability.
•Enable engineering teams through GitHub Enterprise, GitHub Actions, GitHub Advanced Security, GitHub Copilot and secure, AI-assisted software delivery practices.
•Establish observability and reliability practices across cloud platforms, applications, AI services and agentic workflows, including telemetry, dashboards, service objectives, runbooks and automated remediation.
•Contribute reusable architectures, automation, tools and delivery patterns that strengthen cloud and AI platform capability.
•Support solution shaping, estimates, proposals, risk assessments and customer presentations, communicating effectively with technical and executive stakeholders.

AzureCloudAIPlatform EngineeringConsultingInfrastructure as CodeGitHubFull-timeOn-siteMelbourne

Core Qualifications

Technical (Must-have)

Soft Skills

CommunicationStakeholder EngagementCommercial AwarenessMentoring

Key Responsibilities

•Lead Azure discovery, advisory and architecture engagements, translating customer objectives into secure and practical platform designs.

•Design and implement Azure platform foundations, including landing zones, identity, networking, governance, policy, security controls and self-service capabilities.

•Build repeatable automation using Infrastructure as Code, GitOps, policy as code and continuous integration and delivery practices.

•Design and deploy AI-ready environments using services such as Azure AI Foundry, Azure OpenAI and Azure AI Search, including retrieval-augmented generation, vector search and secure data integration patterns.

•Develop and support governed agentic workflows, including tool integrations, human oversight, lifecycle controls, testing, monitoring and cost management.

•Establish responsible AI practices, including model and agent governance, data and prompt controls, security guardrails, consumption management and operational accountability.

•Enable engineering teams through GitHub Enterprise, GitHub Actions, GitHub Advanced Security, GitHub Copilot and secure, AI-assisted software delivery practices.

•Establish observability and reliability practices across cloud platforms, applications, AI services and agentic workflows, including telemetry, dashboards, service objectives, runbooks and automated remediation.

•Contribute reusable architectures, automation, tools and delivery patterns that strengthen cloud and AI platform capability.

•Support solution shaping, estimates, proposals, risk assessments and customer presentations, communicating effectively with technical and executive stakeholders.