AI Product Manager, Enterprise Operations

URUS is a global family of agricultural businesses at the heart of the dairy and beef industry. Operating in more than 80 countries, we unite expertise in genetics, reproduction technologies, animal health, and precision-management data to advance our vision: Better Cows for a Better World.

Reporting to the Director of Artificial Intelligence, the AI Product Manager, Enterprise Operations will turn complex business challenges into practical, responsible, and measurable AI-enabled solutions. You will partner with leaders across Commercial, Finance, People, and other corporate functions to identify high-value opportunities, prioritize use cases, develop business cases, and guide solutions from discovery through adoption and performance measurement. This role brings together product management, process improvement, and change leadership with the practical AI knowledge needed to assess value and risk, ask the right questions, and collaborate effectively with technical teams.

What You’ll Do

• Partner with business leaders and functional teams to uncover operational challenges, inefficiencies, and opportunities where AI could create value.

• Evaluate and prioritize AI opportunities based on business impact, technical feasibility, data readiness, risk, adoption effort, and strategic alignment.

• Develop clear problem statements, business cases, product requirements, user stories, acceptance criteria, and success measures.

• Own and continuously refine the AI product roadmap and opportunity backlog, ensuring work is appropriately prioritized, sequenced, and ready for execution.

• Guide AI-enabled solutions from discovery and experimentation through proof of concept, MVP, production release, adoption, measurement, and iteration.

• Collaborate with AI engineers, data scientists, architects, project managers, business stakeholders, and external partners to design and deliver effective solutions.

• Assess data readiness, governance, privacy, security, model quality, implementation risk, and long-term support needs before solutions move into production.

• Lead adoption efforts through stakeholder engagement, communication, education, training, documentation, and feedback.

• Establish performance measures that connect AI initiatives to outcomes such as operational efficiency, cost savings, quality, user adoption, and business impact.

• Communicate priorities, progress, risks, tradeoffs, ROI, and recommendations to business and technology leaders.

What You’ll Bring

• Bachelor’s degree in business, technology, computer science, data science, engineering, or a related field, or equivalent relevant experience.

• At least three years of experience in product management, business transformation, process improvement, technology implementation, or a related role.

• Experience delivering AI/ML-enabled products, workflows, automation, or internal tools from discovery through implementation and adoption.

• Product ownership experience, including managing roadmaps and backlogs, writing user stories, defining acceptance criteria, and prioritizing work.

• Demonstrated ability to analyze business processes, identify improvement opportunities, and translate needs into practical technology solutions.

• Experience developing business cases and measuring outcomes such as ROI, cost savings, productivity, quality, or user adoption.

• Experience leading cross-functional initiatives involving both business and technical stakeholders.

• Experience supporting organizational change through adoption planning, training, communications, and feedback.

• Practical knowledge of generative AI, large language models, AI-enabled automation, and emerging agentic capabilities.

• Strong communication skills and the ability to make complex technology concepts understandable to nontechnical audiences.

Experience That Could Set You Apart

• An advanced degree or relevant certification in product management, AI, data science, business, or change management.

• Knowledge of agriculture, animal health, dairy, beef, or another data-rich industry.