Sr Product Manager II, Agentic AI Development

Hands‑On Agentic AI Development Partner with GP stakeholders to identify meaningful workflow problems and translate them into clear agent behaviors, triggers, and outputs with defined success measures. Deliver agents that are ready for scale‑up, including documentation, configuration details, UX notes, known limitations, and clear handoff artifacts for production deployment and lifecycle support. Apply engineering discipline even in low‑code contexts: versioning, repeatable builds, structured testing, and continuous improvement based on usage data and feedback. Provide hands‑on mentoring sessions (office hours, design reviews, build reviews) to raise overall AI fluency and agent development quality across GP. Contribute to lightweight governance that prevents uncontrolled agent sprawl by enforcing basic standards: ownership, documentation, UX consistency, monitoring, and retirement planning. Treat UX as a first‑class design constraint: build agent interactions that are intuitive, predictable, and embedded naturally into GP workflows. Conduct lightweight user research (interviews, workflow observation, usability testing) and iterate quickly to remove friction and increase adoption. Define measurable outcomes (e.g., time saved, cycle time reduction, reduced rework, improved compliance workflow completion) and continuously tune agent behavior to improve results. Master's degree required in Business, Supply Chain, Information Systems, Computer Science, or a related field. Additional certifications or advanced education in AI, automation, analytics, or product management strongly preferred. Proven track record of developing and shipping agentic AI solutions—with evidence of end‑to‑end delivery (design, build, iteration, and release) that achieved user adoption and measurable outcomes (e.g., productivity gains, cycle time reduction, compliance improvements). Strong track record partnering directly with business users to discover workflow pain points, prototype solutions, and iterate based on feedback—prioritizing UX and sustained adoption. Demonstrated ability to lead innovation through structured exploration—forming hypotheses, running experiments, learning quickly, and turning insights into scalable patterns, reusable components, or standardized approaches for broader adoption. Experience coaching and enabling non‑technical users and leaders to adopt AI and, where appropriate, develop solutions within a Citizen Developer Framework (structured enablement model that empowers employees as AI users and makers while reducing duplication and improving reuse). Experience collaborating across functions (including IT and governance teams) to move solutions from prototype to scalable deployment. Builder mindset with strong product thinking: value hypotheses, iteration loops, and outcome measurement. User Experience‑obsessed: able to translate complex workflows into simple, intuitive agent experiences. Comfortable operating in ambiguity and rapidly evolving AI capabilities. Strong communication and coaching ability—able to raise overall AI fluency across GP team members and leaders. Familiarity with Procurement, Supply Chain, or Operations environments is a plus, enabling faster discovery of impactful use cases and more intuitive agent design.