Engagement Lead
On-siteMelbourne, Victoria, Australia
Job Summary
Structure and lead end-to-end AI-native advisory engagements, translating client high-level goals into actionable workstreams, milestones, and decision-ready outputs. Ensure all deliverables are accurate, logically consistent, and technically feasible by serving as the final line of defense for business relevance and strategic alignment. Define collaboration models across teams and AI agents, breaking down ambiguous problems into structured tasks while driving execution from initial ideas to final implementation. Capture and scale repeatable workflows and delivery assets to contribute to the organization's growing library of engagement models and decision frameworks.
Required Qualifications
- Experience in orchestrating AI-Native Delivery
- Experience in designing how AI is used across the engagement: Analysis; Scenario modeling; Code and workflow generation; Documentation
- Experience in delegating work effectively to AI while maintaining quality and judgment
- Experience with Client Delivery Leadership: Act as primary counterpart to - CTO / CIO, Program leads and Product/engineering leaders
- Experience with translating advisory recommendations into practical execution paths
- Experience with navigating constraints and tradeoffs in real time, identify delivery risks early (technical, organizational, or commercial)
- Experience with ensuring recommendations are grounded in what can actually be delivered
- Professional Experience: Requires 8–15 years of experience in consulting, product, and/or technology delivery roles
- Proven Leadership: Demands a track record as an Engagement Manager, Project Leader, or Product/Engineering leader heading complex, end-to-end initiatives
- Ambiguity Management: Ability to lead multi-disciplinary teams in highly ambiguous environments and break complex problems down into actionable work
- Strategic Thinking: Thinks critically in terms of hypotheses, trade-offs, and final business outcomes
- Execution & Accountability: Drives execution with sharp focus, maintaining a strong balance between rapid pace and high quality
- Systems Thinking: Deeply understands how business processes, technology, and data interconnect to reason through end-to-end flows and dependencies
- AI Fluency: Comfortably utilizes AI tools to accelerate analysis, generate outputs, and maximize delivery efficiency
- AI Critical Thinking: Possesses the judgment to know when to trust AI outputs—and when to validate or question them
- Stakeholder Management: Works fluidly and effectively across both business and technology stakeholders
- Clear Communication: Communicates information in a clear, concise, and impactful manner
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