Artificial Intelligence

• Design, build, and operationalize agentic AI solutions in production.
• Lead technical discovery and translate business problems into engineering deliverables.
• Write production-grade code and work within enterprise release governance.
• Build evaluation suites for production observability and integrate solutions with client identity.
• Stay engaged through production iteration cycles and provide support documentation.

Forward Deployed Engineer, Agentic AI

• You’ll be involved in a mix of technical delivery, AI development, and problem solving, including:
• Build visual workflow and routing solutions
• Connect systems via APIs and map data between platforms
• Develop serverless functions using JavaScript/Node.js or Python
• Design and refine conversational flows for virtual agents in a CX (Customer Experience) environment.
• Train intent models and support natural language understanding (NLU)
• Create and optimise prompts for AI-driven experiences
• Ingest and structure knowledge base content for AI Agent use
• Conduct functional and integration testing
• Troubleshoot issues and continuously improve solutions

Graduate AI, CX Engineer

• Own and deliver change strategies for major transformation programs, designed around people experience and adoption.
• Lead change activity across multiple workstreams end to end, covering stakeholder engagement, communications, training and adoption.
• Translate program objectives into practical, sequenced change plans that align to business priorities and can be executed.
• Design and deliver training plans that build genuine capability across impacted teams.
• Developing project communication plan and write project communications that are clear, effective and aligned to corporate affairs standards.
• Identify risks, issues and dependencies that threaten adoption early, escalate where needed and own the mitigations.
• Prepare senior leaders and sponsors with the insights, materials and recommendations they need to make decisions and show up credibly.
• Manage the integration of change activity across strategy, design and implementation phases, keeping dependencies and sequencing tight.
• Build change capability across the program, raising the bar and embedding sustainable practice.
• Build and maintain strong, trusted relationships with stakeholders and teams through collaboration, credibility, and consistent delivery.

Senior Change Manager – AI Business Transformation

• Deliver high-quality, engaging workshops and training sessions for corporate learners on OpenAI Codex, frontier models, AI-assisted software development, prompt engineering, and agentic workflows.
• Teach learners how to use Codex across practical workflows, including reading and understanding codebases, generating and editing code, debugging, writing tests, reviewing pull requests, working through IDE or CLI-based workflows, and delegating coding tasks to cloud agents.
• Introduce learners to OpenAI’s frontier model ecosystem, including the Responses API, reasoning models, multimodal capabilities, tool use, function calling, file search, web search, structured outputs, and agent-based application patterns.
• Lead training sessions with confidence for mixed audiences, including software engineers, business users, product managers, operations teams, and senior leaders.
• Adapt training examples, exercises, case studies, and demos to suit each client’s industry, technical maturity, business objectives, and internal workflows.
• Build and deliver live demonstrations showing how AI tools can support real work, such as code review, bug fixing, technical documentation, data analysis, workflow automation, knowledge retrieval, and AI-assisted product development.
• Work with Skills Union and client stakeholders to understand training needs, learner profiles, adoption barriers, and desired business outcomes before and during delivery.
• Guide learners through hands-on activities, troubleshoot common setup or workflow issues, and help participants build confidence using AI tools responsibly and effectively.
• Evaluate learner progress through exercises, projects, reflections, and feedback. Provide clear recommendations for continued adoption after training.
• Teach practical considerations around data privacy, security, intellectual property, human review, hallucination risk, model limitations, and responsible enterprise deployment.
• Stay current with OpenAI product updates, Codex capabilities, frontier model releases, and AI adoption practices.

Technical AI Instructor

• Engage in conversations with a real-time speech-to-speech AI model
• Evaluate performance based on speech recognition, audio quality, conversation flow, and content accuracy
• Provide accurate and consistent ratings based on project guidelines
• Complete assigned tasks within the given timelines
• Each conversation will last approximately 8 to 10 minutes.

Conversational Speech AI Evaluator, Australia

• Partner with teams across MYOB including People Experience, Finance, Technology and Product to deeply understand workflows, challenges and opportunities
• Redesign and optimise ways of working through AI-first approaches, embedding human and agent collaboration into everyday work
• Leverage and extend MYOB’s AI stack, integrations and tooling to deliver scalable, high-impact solutions
• Coach and enable teams to confidently, safely and effectively adopt new AI-enabled ways of working
• Measure and communicate the impact of AI enablement through improvements in speed, quality, throughput and overall team experience

Senior AI Enablement Engineer

• Lead end-to-end delivery of digital, data, and AI-enabled transformation programs
• Shape innovative solutions to complex, ambiguous problems
• Translate strategy into practical, scalable delivery
• Engage and influence senior government and executive stakeholders
• Work across technical and business teams to drive results
• Identify and scale emerging technology opportunities (AI, automation, data)

Senior Manager – Digital & AI Transformation

• This role sits at the intersection of People, Technology, and AI, helping us transform how our People team operates through intelligent AI and automation
• The AI Enablement Partner is a specialist role within our HR Tech team , focused on designing, building, and scaling intelligent automation across the People technology ecosystem
• This role bridges the gap between what our systems can do today and what they should be doing tomorrow—using low-code automation platforms, AI agents, and smart integrations to eliminate repetitive work and accelerate decision-making
• You'll also partner directly with teams across the People org — understanding how they work, and co-designing AI and automation solutions that actually fit their day-to-day
• At the moment, this role is focused on: Designing and building automations that remove repetitive work across our People tech stack
• Developing AI-powered solutions like copilots, agents, and intelligent workflows to improve self-service and support
• Working with our IT team to connect systems like Workday, SmartRecruiters, and CultureAmp through scalable integrations
• Ensuring clean, structured, analytics-ready data through automation and validation workflows
• Acting as a force multiplier across the PSA team — supporting, troubleshooting, and scaling impact
• Continuously improving automation performance, reliability, and ROI across the ecosystem
• Serve as buffer capacity for other HR Systems Analyst roles during peak periods

AI Enablement Partner – HR

• Define and own the enterprise AI vision, strategy, and multi-year roadmap
• Identify and prioritise high-value AI use cases across functions - balancing impact, feasibility, and speed
• Establish the AI operating model: governance, frameworks, tooling, and ways of working
• Monitor AI trends and emerging technologies to keep Airtasker ahead of the curve
• Lead end-to-end delivery of AI initiatives - from ideation through to implementation and optimisation
• Define and track success metrics: ROI, productivity gains, and cost efficiencies
• Build and scale a high-performing AI transformation function
• Partner with the CEO, CTO, and ELT to align priorities and secure investment
• Build credibility and trust with both executive and technical audiences
• Work cross-functionally across Product, Engineering, Data, People, Finance, and Operations
• Embed AI solutions into day-to-day workflows - not just deploy them
• Lead organisation-wide change management, capability uplift, and behavioural transformation
• Drive genuine adoption by bringing people on the journey, not just communicating at them

Director, AI Strategy – Transformation

• Ensure nbn’s AI initiatives deliver meaningful, measurable, and sustained business value
• Lead frameworks and disciplines for value definition, tracking, and realisation
• Act as the central point for enterprise execution and clear delivery roadmap
• Partner with senior leaders to ensure standard delivery and evolving value expectations

General Manager – AI Value and Delivery

• Shape and embed AI-ready processes that support simplification and digitisation ambitions
• Lead large-scale, end-to-end process and workflow redesign
• Drive measurable improvements in operational efficiency, time savings and cost reduction
• Enhance enterprise approach to process excellence through consistent redesign playbook

General Manager – AI Process Redesign

• Provide Line 1 Risk view on Data, Analytics and AI Risks, including responding to evolving regulatory and industry expectations
• Ensure effective Line 1 oversight and governance of the implementation and ongoing adherence to the Group policies and standards for Data, Analytics and AI
• Provide leadership to the Group and Divisional teams to ensure policies and standards are translated into sound controls and assurance activities to enable effective risk management and timely escalation and resolution of material risks/issues
• Work across the three lines of defence to develop and deliver the Data and AI Risk and Control framework and associated assessments
• Establish and manage a clear cadence of risk governance forums to support identification, monitoring, remediation and reporting of risks and controls
• Lead Risk & Control Self‑Assessment and assurance engagements with risk and control owners, ensuring work is well scoped, planned and delivered to a high standard, and produces reliable, high‑quality management information on risks, controls, issues and actions.
• Produce high‑quality, targeted risk reporting for senior management and governance forums, delivering clear narratives on key risks and concise updates on the status of risks, controls, issues and actions.
• Build strong partnerships with Line 2 Risk, Internal Audit, Privacy and Compliance to embed an integrated, end‑to‑end risk management approach

Senior Manager – Data, Analytics and AI Risk Management

• AI-Driven Business Analysis: Deploy and orchestrate AI agents to analyse legacy codebases, extracting business logic and generating comprehensive, modern requirement documents through reverse engineering.
• AI-Driven Quality Assurance: Design prompts and agent workflows that automatically generate, execute, and validate test cases against the modernised system, ensuring robust quality checks.
• Prompt Engineering & Orchestration: Refine LLM prompts and manage agent frameworks to ensure high-accuracy outputs, minimising AI hallucinations in both requirements and test results.
• Validation & Human-in-the-Loop: Act as the critical bridge between AI output and reality, manually validating generated requirements and test coverage to ensure alignment with business objectives.
• Collaboration: Work closely with cross-functional teams, including developers, Scrum Masters, and QA specialists, to ensure seamless integration of AI-driven processes into the software development lifecycle.

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