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Metro location and reputable VC backing increase applicant density, but niche AI product focus limits competition.
Role requires B2B and AI product experience, making cross-industry transfers moderately feasible.
No explicit years but technical product and AI domain requirements create moderate filtering.
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Own and execute the data and AI strategy roadmap to enable AI-driven field service products.
Define data requirements, write engineering-ready epics and stories, and guide data pipeline and LLM interface architecture.
Lead cross-functional collaboration across Platform, Data Platform, Engineering, Design, Security, and Legal to build scalable, compliant data products and analytics solutions.
Strong B2B experience.
Hands-on proficiency in Scrum and Jira with experience writing epics and user stories.
Technical fluency to challenge engineering teams on architecture and data models.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building or maintaining data products such as data warehouses or data lakes.
Familiarity with AI-driven products and analytics, including LLM/agent interfaces and usage measurement.
Comfortable working in globally distributed, cross-functional product teams with Scrum and Scrum of Scrums practices.