About the AI Business Unit The Artificial Intelligence (AI) function will be a key enabler to the Clean Energy Regulator's (CER) digital transformation, driving the responsible, ethical, and effective use of AI to enhance regulatory, operational efficiencies and policy outcomes. Under the leadership of the Chief AI Officer, the team will support AI usage across the Agency, aligned with the Agency's strategic objectives and whole-of-government digital priorities. With expertise in artificial intelligence principles, practices, and technologies, the team ensures AI initiatives are designed and deployed in ways that are scalable, secure, and aligned with the Agency's values and operational goals. This includes applying robust AI governance frameworks, ensuring model integrity and performance, and integrating AI capabilities into core business processes to support sustainable and responsible innovation. The team operates in alignment with Agency program and BAU investment prioritisation and IT and data architecture governance arrangements. The AI Team is structured around two teams: AI Technical Capability Development This section leads the design, development, and deployment of AI solutions across the Agency. It provides technical leadership, supports pilot programs, and ensures alignment with IT architecture and data governance. The team is responsible for delivering robust solutions, developing and refining AI models, and integrating AI platforms into the Agency's digital environment. Their work ensures that AI systems are secure, scalable, and aligned with CER architecture standards, supporting both operational efficiency and innovation. AI Adoption This section focuses on enabling the workforce to confidently and ethically engage with AI technologies. It delivers training, builds communities of practice, and supports the development of AI use cases through business analysis and stakeholder engagement. This section ensures AI is adopted in a way that is inclusive, people-centric, and aligned with the Agency's values and operational goals. Together, these teams support the Chief AI Officer in delivering strategic leadership, uplifting AI literacy, managing risk, and ensuring the Agency remains adaptive and innovative. About the Section The AI Technical Team plays a pivotal role in shaping the Agency's approach to artificial intelligence by overseeing the complete lifecycle of AI solution development. This includes the initial design phase, where the team collaborates to identify business requirements and suitable AI technologies. This is through the development, deployment, and ongoing optimisation lifecycle of these solutions. Their remit extends to providing expert technical leadership, ensuring that all AI initiatives are grounded in best practice and adhere to the Agency's overarching enterprise IT architecture and data governance frameworks. In addition to delivering secure, scalable, and robust AI systems that enhance operational efficiency and drive innovation, the AI Technical Team actively supports pilot projects. This involves coordinating logistics, preparing user guides, and working closely with the AI adoption section. This is achieved though gathering feedback from stakeholders for further analysis and refinement of AI tools. The team is also responsible for maintaining technical documentation, updating system registers, creating architectural artefacts, and managing the backlog of AI items. The key duties of the position include Under limited direction, the APS Level 6 Senior AI Technical Officer will: Contribute to the design, development, deployment, and optimisation of AI solutions, ensuring alignment with enterprise IT architecture and data governance frameworks. Provide technical expertise and support for pilot programs, including coordinating logistics and preparing user documentation. Build and lead the development of small-scale AI solutions such as agents based on Microsoft CoPilot Studio. Build and maintain effective relationships with internal and external stakeholders, including senior executives, technical specialists, policy makers, and external partners, to facilitate collaboration and achieve strategic agency outcomes. Deliver training and support communities of practice to build AI literacy among technical practitioners. Assist in developing AI use cases through business analysis and stakeholder engagement, enabling the workforce to confidently and ethically use AI technologies. Exercise sound judgement and initiative in managing risks and driving innovation. Ensure AI systems are secure, scalable, and aligned with Agency architecture standards to support operational efficiency and responsible, sustainable innovation. Support the AI Technical Manager in managing team and individual performance, coaching and developing staff, and leading teams through change. Contribute to strategic leadership to ensure the Agency remains adaptive and innovative. Qualifications/Experience Essential: Demonstrated ability to design, configure, and deploy Microsoft Copilot agents tailored to business needs, including summarisation, document drafting, and decision support. Experience in developing and deploying artificial intelligence and machine learning models. Hands-on experience with Microsoft Copilot Studio and Azure AI Foundry. Proven capability in working with large datasets and building scalable data pipelines. Practical understanding of ethical and responsible AI principles, particularly in government or regulated environments. Familiarity with Agile delivery methodologies and DevOps practices, including CI/CD. Experience leading small technical teams and mentoring junior staff. Knowledge of integrating Copilot agents with enterprise data sources such as SharePoint, Outlook, Microsoft Teams, and Microsoft Graph. Highly Desirable: Relevant tertiary qualifications in computer science, information technology or engineering, Certifications in Azure-related skills (e.g. Azure AI Engineer, Azure Data Scientist, Azure Solutions Architect). Demonstrated experience in designing, developing, and deploying AI/ML systems in complex enterprise environments. Experience in maintaining and iterating agent prompts, workflows, and templates to improve relevance and usability. Experience configuring and deploying Azure Large Language Models (LLMs) and Small Language Models (SLMs) for business use cases. Ability to integrate Azure AI solutions for scalable, secure, and compliant performance.
