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Manager, Software Engineering

Dbtlabsinc
9 days ago
Full-time
Remote
Worldwide
Remote Engineering

About Us 

dbt Labs is the pioneer of analytics engineering, helping data teams transform raw data into reliable, actionable insights. Since 2016, we’ve grown from an open source project into the leading analytics engineering platform, now used by over 90,000 teams every week, driving data transformations and AI use cases. 

As of February 2025, we’ve surpassed $100 million in annual recurring revenue (ARR) and serve more than 5,400 dbt Platform customers, including AstraZeneca, Sky, Nasdaq, Volvo, JetBlue, and SafetyCulture. 

We’re backed by top-tier investors including Andreessen Horowitz, Sequoia Capital, and Altimeter. At our core, we believe in empowering data practitioners:

  • Reliable, high-quality data is the fuel that propels AI-powered data engineering.

  • AI is changing data work, fast. dbt’s data control plane keeps data engineers ahead of that curve.
  • We empower engineers to deliver reliable, governed data faster, cheaper, and at scale.

dbt Labs is now synonymous with analytics engineering, defining the modern data stack and serving as the data control plane for enterprise teams around the world. And we’re just getting started.. We’re growing fast and building a team of passionate, curious people across the globe. Learn more about what makes us special by checking out our values.

About the Team

You'll lead the AI Platform Team, the engine room for agentic workflows at dbt Labs. This team doesn't just build features; it builds the Agentic Platform that powers both our internal AI features and external AI integrations.

In this role, you can expect to:

  • 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, t