Australian Citizens residing in Australia only respond.

Job details

The AI Business Enablement Specialist builds a deep understanding of business problems, the people, process and tools, how work is done, and the ability to inspire how work can be done within the Australian Federal Government content and develop AI prototypes to demonstrate the 'art of the possible', wherever relevant. The AI Business Enablement Specialist will also work with data/AI capabilities, translating them into clear, testable user stories and acceptance criteria for multi‑disciplinary agile teams. They shape AI‑enabled features and services that are ethical, transparent and compliant, and ensure the right human‑in‑the‑loop controls, explainability and auditability are in place across the AI lifecycle.

Key duties and responsibilities

Key Responsibilities

• Lead rapid prototyping sessions to inspire the business to rethink business processes, roles and responsibilities for staff and demonstrate technology capabilities using tools such as Microsoft Copilot, Microsoft PowerPlatform and Azure Foundry.
• Elicit, analyse and document business, data and AI requirements; decompose into epics, features and user stories with testable acceptance criteria.
• Define non‑functional needs specific to AI (transparency, safety, robustness, latency, security, privacy).
• Map processes/decision points to decide AI vs rules‑based and specify human authority levels and HITL checkpoints.
• Co‑design evaluation frameworks for AI features (ground‑truth datasets, baselines; monitor performance, drift and fairness over time).
• Partner with data scientists/engineers & product owners to turn outcomes into model objectives, features and data constraints.
• Lead workshops, discovery and backlog refinement; produce service blueprints & future‑state workflows across teams.
• Develop acceptance criteria and test cases for AI/ML features (shadow testing, A/B trials, red‑teaming, rollback plans).
• Document prompt/model assumptions, guardrails and safety constraints (retrieval scope, prompt patterns, redaction).
• Contribute to privacy threshold assessments / PIAs, threat risk assessments and records management of AI artefacts.
• Ensure alignment with CER Internal AI Policy, AI Governance Framework, and Data Governance Framework/Data Policy; coordinate approvals with governance forums.
• Support change management, comms & training for AI‑enabled processes and tools (e.g., Copilot scenarios).
• Participate in Communities of Practice and continuous improvement across relevant areas of CER.

Qualifications/Experience

The AI Business Enablement Specialist must have:

• 3+ years as a BA/Systems Analyst in digital/service delivery, including agile teams.
• Hands‑on experience supporting AI‑enabled products within the Microsoft Stack (ML, NLP/LLMs, Copilot or intelligent automation, including PowerPlatform suite) from discovery to delivery.
• Proven ability to write testable stories and acceptance criteria for AI features (incl. evaluation metrics & guardrails).
• Working knowledge of responsible & secure AI (privacy‑by‑design, human oversight, explainability, bias mitigation).
• Workshop facilitation and stakeholder engagement across technical and non‑technical audiences.
• Proficiency with Azure DevOps and Miro (or equivalent).
• Excellent written and verbal communication; able to influence decisions with evidence and prototypes.

Criteria

The buyer has specified that each candidate must provide a response to each criterion. Each response is limited to 3000 characters.

Essential criteria

• 1.Candidate demonstrates strong capability to elicit, analyse and translate business needs into clear process maps, user stories, acceptance criteria and delivery-ready artefacts for multidisciplinary teams.
• 2.The extent to which the candidate demonstrates practical experience using AI-enabled tools, preferably within the Microsoft stack, (including Microsoft Foundry, Copilot Studio and PowerPlatform) to explore business problems, rapidly prototype solutions, and show how AI can improve workflows, decision-making or service delivery.
• 3.The extent to which the candidate demonstrates understanding of responsible AI, privacy, security, human oversight, explainability, bias, records management and governance requirements, and can apply these considerations to real business scenarios.
• 4.Candidate demonstrates ability to facilitate workshops, engage technical and non-technical stakeholders, communicate complex AI concepts clearly, influence adoption, and support change, training and continuous improvement.