Own the company-wide data strategy and lead the transition from traditional BI to AI-driven BI. Build trustworthy data infrastructure, semantic and metrics layers, agent-based analytics, Git-based workflows, and MCP data access. Lead analytics, experimentation, impact measurement, and AI quality evaluation while partnering with product, marketing, finance, operations, and engineering. Manage a data engineer and represent the data function at a senior leadership level.

Build and own customer support operations, including QA, training, knowledge management, hiring processes, AI tooling, workflows, escalations, and support metrics. Partner with support, product, and development teams to improve member experiences, automate processes, maintain accurate resources, and determine where AI or human support is most appropriate. Coach agents and develop scalable systems for a growing relationship support platform.

The Generative AI Engineer will design AI architecture, build production features, lead prompt design, collaborate with teams, and stay updated with the GenAI ecosystem.