Manager, Software 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, 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. Mandatory Skills 3+ years in people management leading high-performing software engineering teams. Experience with Agentic Architectures: You understand the lifecycle of an agentic loop (Plan -> Act -> Observe) and how to build infrastructure that supports it. Technical Breadth in APIs & Protocols: Deep experience with API design, and ideally, familiarity with emerging standards like MCP (Model Context Protocol) or OpenAI Function Calling. Software Engineering Fundamentals: You have a strong POV on how to maintain dbt’s "Analytics Engineering" rigors (testing, CI/CD) in an AI-driven world. You are a good fit if you have: A passion for Developer Tools: You understand the workflow of a data engineer and how tools like Claude Code or Codex are changing that workflow. Experience with Orchestration: You’ve built systems that manage state and context for LLMs. Strategic Collaboration: You can partner with external AI labs and internal teams to ensure dbt is the preferred "data context" layer for all major LLMs. You’ll have an edge if you have: Direct experience building or contributing to MCP servers. Experience in the "Modern Data Stack": You understand the importance of the dbt Semantic Layer and how it acts as a "source of truth" for AI. Excellent written communication skills: Essential for a remote-first culture and for documenting the "rules of engagement" for AI agents. Compensation & Benefits Salary :We offer competitive compensation packages commensurate with experience, including salary, equity, and where applicable, performance-based pay. Our Talent Acquisition Team can answer questions around dbt Labs' total rewards during your interview process. In select locations (including Boston, Chicago, Denver, Los Angeles, Philadelphia, New York Metro, San Francisco, DC Metro, Seattle, Austin), an alternate range may apply, as specified below. The typical starting salary range for this role is: $186,000 - $225,000 USD The typical starting salary range for this role in the select locations listed is: $206,000 - $250,000 US Equity Stake Benefits - dbt Labs offers: Unlimited vacation (and yes we use it!) 401k w/3% guaranteed contribution Excellent healthcare Paid Parental Leave Wellness stipend Home office stipend, and more! *Equity or comparable benefits may be offered depending on the legal limitations Our Hiring Process (All Video Interviews) Interview with a Talent Acquisition Partner (30 Mins) Technical Interview with Hiring Manager (60 Mins) Team Interviews ( 4 rounds, 45 Mins each) If you’re passionate about building well-designed, high-impact software, we’d love to hear from you! dbt Labs is an equal opportunity employer, committed to building an inclusive team that welcomes diverse perspectives, backgrounds, and experiences. Even if your experience doesn’t perfectly align with the job description, we encourage you to apply—we value potential just as much as a perfect resume. Want to learn more about our focus on Diversity, Equity and Inclusion at dbt Labs? Check out our DEI page . dbt Labs reserves the right to amend or withdraw the posting at any time. For employees outside the United States, dbt Labs offers a competitive benefits package. RSUs or comparable benefits may be offered depending on the legal or country limitations. Privacy Notice Supplement to Privacy Notice - Californians Supplement to Privacy Notice - EEA/UK

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