• Build, lead, and coach a team of 5–8 engineers focused on building a robust, scalable platform for AI agents. • Architect the "Agent-First" Experience: Move dbt beyond a UI-driven tool by building the APIs and services required for agents to reason, plan, and execute within the dbt ecosystem. • Define dbt’s MCP Strategy: Lead the development of dbt MCP tools that allow Claude, Codex, and other LLMs to fetch context, validate SQL, and understand metrics without leaving their development environment. • Bridge Platform and Product: Partner with product teams to ensure that the AI Platform provides the necessary primitives (memory, tool-calling, and reasoning loops) for dbt’s specific agentic use cases. • Coach engineers in building "Agent-ready" codebases—focusing on deterministic outputs from a non-deterministic world and the nuances of tool-use optimization. • Drive Technical Excellence: Establish the standards for how agents should interact with dbt Cloud, ensuring security, governance, and auditability are never compromised for autonomy.