Manager, AI Transformation ANZ

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve.

This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

This newly created position is accountable for the AI agenda across Lilly Australia’s commercial business. You will determine which AI solutions are developed, build many of them directly, and lead sales, marketing and analytics teams in adopting AI effectively as part of their everyday work. The role combines strategic planning, hands-on development, implementation and coaching. At times you will be developing Python code and prompt chains to convert a complex analytical process into a working AI tool.

At others, you will be working with a sales team to help them use that tool well and to critically assess its outputs. You will lead through influence and be accountable for accelerating commercial AI adoption across Australia and New Zealand.

• AI strategy and roadmap:
  Develop and maintain a prioritised roadmap of AI solutions for the commercial business, aligned to global policy and strategy. Act as the trusted adviser on where AI will and will not deliver value, and the rationale behind each position. Track and report on both adoption and business impact.
• Solution development:
  Design, build and test AI tools using Python, SQL and prompt engineering with enterprise AI models. Lead the establishment of an AI‑ready data foundation. Integrate AI capability into the analytics environment the business already uses. Evaluate and select external vendors where purchasing is preferable to building. Replace ad hoc data requests with governed, standardised extracts built on agreed definitions.
• Governance and risk management:
  Establish and own the local AI governance framework for commercial use cases. Define how solutions are validated prior to release and monitored thereafter, including quality controls, early‑warning indicators and rollback procedures. Maintain the AI use‑case register, providing a single view of how and where AI is applied across the commercial function. Own the semantic layer, metric definitions and master‑data rules, ensuring field teams, managers and AI tools operate from a single source of truth.
• Adoption and capability building:
  Design and deliver training and coaching for field sales, managers, marketing and analytics colleagues, with the objective of building a self‑sufficient field force. Develop change and implementation plans for each rollout and lead associated communications. Support affiliate‑wide AI programmes and the internal advocate network.

Several AI solutions are live and adopted, with users able to articulate the benefits to their work. A working framework for developing, training and deploying AI solutions is in place and in active use across the business. Global solutions are assessed on merit, with those that benefit local patients and customers implemented, and others declined with feedback provided. The field force uses AI confidently and independently, without reliance on central analytics support.

• Essential Demonstrated success deploying large-scale AI solutions within a large multinational organisation, including adoption and change…