6 days ago

AI Technical Lead

National Heavy Vehicle Regulator

Brisbane City

6 days ago

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AI Technical Lead

The National Heavy Vehicle Regulator (NHVR) is seeking an AI Technical Lead in Brisbane to design, engineer, test, and deploy approved AI-enabled solutions within its Microsoft Copilot stack. This 2-year max term role requires hands-on experience with Microsoft 365 Copilot, Copilot Studio, Azure AI Foundry, and Azure AI Search, along with strong software engineering and integration skills. The position offers a competitive salary package of $166,662.51 plus superannuation and a hybrid working environment.

Core AIHybridContractSeniorMicrosoft 365 CopilotMicrosoft Copilot Studio

AI Technical Lead

Apply

Core AIHybridContractSeniorMicrosoft 365 Copilot

Salary

Not specified

Work Location

Brisbane City, Queensland, Australia, AU

Work Model

Hybrid working environment - up to 2 days from home

Employment Type

Full-time, 2-year max term engagement

Experience Level

Mid-Senior level

Contract Length

24 months

Core Qualifications

Technical (Must-have)

Microsoft 365 CopilotMicrosoft Copilot StudioAzure AI FoundryAzure AI SearchGenerative AILarge Language ModelsAgentsGroundingRetrievalPrompt designContext designModel behaviourAI evaluationResponsible AIAPIs

Soft Skills

CollaborationProblem-solvingCommunicationMentoringKnowledge sharingTechnical judgement

Preferred Qualifications

Technical (Nice-to-have)

Azure AI servicesMicrosoft 365 extensibilityRetrieval-augmented generationKnowledge-grounded AIAgentic AIConversational AIAI monitoringAI observabilityMicrosoft GraphMicrosoft Power PlatformDataverseEnterprise development languagesMicrosoft certifications

Key Responsibilities

•Design and implement solutions using approved capabilities, including Microsoft 365 Copilot, Microsoft Copilot Studio, Azure AI Foundry, Azure AI Search, and other approved AI services.
•Apply practical engineering knowledge of generative AI and large language models, including grounding, retrieval, prompt and context design, agents, model behaviour, evaluation, safety controls, human oversight, and financial acumen across AI consumption.
•Collaborate with Enterprise and Solution Architecture to apply approved AI principles, patterns, standards, and guardrails in practical solution delivery.
•Provide evidence-based technical advice on feasibility, cost effectiveness, limitations, delivery effort, data requirements, risks, and support implications of proposed AI use cases.
•Establish repeatable engineering practices for prototyping, source control, configuration management, testing, deployment, observability, documentation, and operational handover.
•Ensure AI-enabled solutions are supportable, measurable, and aligned with approved security, privacy, information governance, data, consumption control, and Responsible AI requirements.
•Build organisational technical AI capability through mentoring, pairing, reusable components, implementation guidance, and knowledge sharing.

AI Technical LeadTransportationLogisticsSupply ChainInformation TechnologyMicrosoft CopilotAzure AIGenerative AIFull-timeContract

Core Qualifications

Technical (Must-have)

Soft Skills

CollaborationProblem-solvingCommunicationMentoringKnowledge sharingTechnical judgement

Key Responsibilities

•Design and implement solutions using approved capabilities, including Microsoft 365 Copilot, Microsoft Copilot Studio, Azure AI Foundry, Azure AI Search, and other approved AI services.

•Apply practical engineering knowledge of generative AI and large language models, including grounding, retrieval, prompt and context design, agents, model behaviour, evaluation, safety controls, human oversight, and financial acumen across AI consumption.

•Collaborate with Enterprise and Solution Architecture to apply approved AI principles, patterns, standards, and guardrails in practical solution delivery.

•Provide evidence-based technical advice on feasibility, cost effectiveness, limitations, delivery effort, data requirements, risks, and support implications of proposed AI use cases.

•Establish repeatable engineering practices for prototyping, source control, configuration management, testing, deployment, observability, documentation, and operational handover.

•Ensure AI-enabled solutions are supportable, measurable, and aligned with approved security, privacy, information governance, data, consumption control, and Responsible AI requirements.

•Build organisational technical AI capability through mentoring, pairing, reusable components, implementation guidance, and knowledge sharing.