• Lead 0→1 AI products from ambiguity to real-world testing – frame problems, define hypotheses, and drive fast build–measure–learn cycles, creating rapid, functional prototypes and using AI as a power tool to explore multiple experience directions, then using what you learn to sharpen product direction and move faster toward the right decisions. • Design novel agentic experiences that transform today’s linear workflows into native, AI-driven journeys – using planning, tool use, and memory to guide customers, not just answer questions. • Partner deeply with engineers, designers, applied scientists, and researchers to explore solution spaces, co-create prototypes, and iterate quickly based on real customer behavior and feedback. • Own metrics, experimentation, and evaluation for your areas , defining success criteria, instrumenting experiences, designing A/B tests, and combining offline metrics, human-in-the-loop review, and online experiments to understand quality, safety, and business impact. • Drive productionization of successful prototypes , specifying requirements for reliability, observability, latency, cost, and failure modes in close collaboration with engineering leads. • Lead cross-functional alignment and responsible AI practices , pulling teams around a clear vision and roadmap, aligning executives and partner teams on priorities and tradeoffs, and addressing data privacy, bias mitigation, and fair housing considerations as we design, evaluate, and deploy AI experiences.