• Build, lead, and coach a team of 5-8 engineers to manage the infrastructure for the dbt platform • Empower your team to achieve big goals by providing product and business context • Dive deep into our product to frame tradeoffs and make decisions about what, how, and when we build • Partner with Product Marketing, Solutions Architecture, and Customer Support to improve migration experiences • Coach engineers in product thinking, quality, and software engineering • Work with peer managers to evolve organizational processes

• 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.

• Own the long-term technical vision for the product engineering organization, ensuring alignment between architectural decisions and business strategy • Guide teams on system design and architecture, knowing when to build, buy, or partner, and when to invest in foundational platform work versus move fast on delivery • Introduce and mature ML/AI-informed capabilities within the platform, partnering with data and product teams to identify where intelligent automation and predictive features can drive outsized user value • Drive the engineering organization's approach to data, both as a product input and as a tool for measuring the health and performance of the systems you build • Set and uphold a high bar for delivery quality, velocity, and reliability across multiple concurrent product workstreams • Establish a mature approach to estimation, technical debt management, and build/buy tradeoffs at an organizational level — not just at the team level • Benchmark software delivery performance against comparable organizations and use that data to set credible, ambitious targets • Lead and continuously improve practices across a geographically distributed engineering organization, including teams working across time zones, ensuring consistency in standards, culture, and output quality without friction for your domestic teams • Lead a multi-layered engineering organization including engineering managers, staff engineers, and individual contributors; you are a builder and developer of leaders • Partner with recruiting and HR to maintain a staffing plan aligned to product priorities — including proactively identifying capability gaps, succession risks, and opportunities to deepen the bench • Set the tone: high expectations, fast pace, psychological safety, and a genuine commitment to making Evermore the career highlight for every engineer here • Coach and sponsor emerging managers and technical leaders, with a demonstrated track record of developing people into bigger roles • Serve as a trusted technical advisor to the CTO and business leadership, translating complex engineering tradeoffs into clear business terms • Gather and analyze engineering performance data to drive organizational decisions, surface risks early, and demonstrate impact • Present and demo work compellingly — to executives, to the board, and across the business — making engineering legible and exciting to non-technical audiences

• Lead the team toward AI-enabled software development • Embed AI tools across the full software development lifecycle (SDLC) • Improve speed, quality, and leverage in software development • Perform development work and review architecture and code with authority