Collaborate with software development through the full lifecycle of AI products • Engage partners, distributors, and global business development to expand adoption of AI capabilities, support joint-solution development, and gather customer insights from diverse markets • Develop and support launch plans with Product Marketing by crafting messaging, writing value propositions, building demos, producing enablement materials, and supporting events • Support Sales, Software Engineering, and Product Marketing with competitive guidance, demos, RFP and RFI responses, and leadership on pricing • Lead and direct customer-facing programs including early adopter programs, betas, advisory sessions, roadmap reviews, and strategic briefings • Maintain actionable feedback loops with Support, Sales, and other teams to identify friction points and opportunities, and synthesize patterns into Productboard for prioritization • Implement operational excellence by maintaining metrics dashboards, and cross-team communication rhythms that support high-quality delivery • Collaborate with Legal, Security, Privacy, and IT to ensure compliance, data sovereignty, accessibility, and responsible AI governance are built into features and user scenarios • Provide internal enablement to increase organizational understanding of AI capabilities • Represent Esri and your product areas at conferences, webinars, user groups, partner summits, and technical communities, communicating product strategy and best practices in geospatial AI • Work closely with engineering, design, and AI platform teams to define technical requirements, choose model integration patterns, validate evaluation metrics, design guardrails, and ensure assistants and agents perform reliably in alignment with Esri AI principles. • Proven ability to define product strategy and collaborate with engineering and design to deliver customer-facing capabilities • Strong written, verbal, and presentation skills for both technical and non-technical audiences • Ability to translate complex GIS and AI workflows into clear, actionable product requirements • Hands-on experience shipping AI-powered features (for example, LLM applications, code assistants, automation) or direct collaboration with teams building them.