AI Engineer, Go-To-Market
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 AstraZenica, 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.
The Opportunity
At dbt Labs, data is the product, the language, and the mission. As our GTM AI Engineer, you'll be the architect behind improving the productivity of our GTM organization through AI-powered and AI-assisted GTM workflows. This is a high-impact, high-agency role sitting at the intersection of engineering, automation, and go-to-market strategy, directly influencing revenue performance, sales productivity, pipeline generation, and conversion rates.
You'll partner with senior GTM leadership and GTM Operations to build the AI-powered infrastructure that defines how dbt Labs goes to market. You'll own the full lifecycle: uncovering inefficiencies, defining what "better" looks like, designing the solution, and building, shipping, and iterating. This role is ideal for someone who thinks like a sales leader, works like a product manager and builds like an engineer, and who wants their work to directly move the needle on revenue growth.
In this role you can expect to:
- GTM owner of building AI capabilities and agents to automate GTM AI use cases and workflow to improve GTM productivity
- Build and deploy AI agents that reduce manual data entry and enhance outbound personalization at scale.
- Enable GTM broader GTM organization AI tools and capabilities and drive deeper adoption by building highest impact AI use cases
- Implement AI-driven outbound programs using tools like Clay, Glean, Claude and LLM APIs to automate account research, data enrichment, and personalized outreach sequences in support of marketing pipeline goals.
- Work directly with GTM operations (revenue ops, marketing ops, enablement etc) to identify productivity improvement opportunities and leverage AI to improve operations and sales productivity
- Experiment rapidly by prototyping AI solutions for current manual processes, measuring results, and iterating to improve GTM funnel conversion improvement.
You are good fit if you have:
- 3–5 years of experience in GTM Engineering, Marketing Operations, Revenue Operations, or a closely related technical role with a track record of driving measurable results.
- Hands-on experience applying AI and automation to GTM problems — you can walk us through concrete examples.
- Proficiency with modern AI and automation tools such as Clay, n8n, Zapier, Gumloop, or GPT/Claude APIs.
- Experience with CRM and marketing platforms such as Salesforce, HubSpot, or Marketo.
- A strong understanding of the sales funnel and the business logic behind the data you're moving.
- A bias toward action — you move from idea → experiment → solution quickly and thrive in ambiguity.
- The ability to communicate clearly with both technical and non-technical stakeholders.
You’ll have an edge if you have:
- Experience with sales platforms like Salesforce, Clari, Gong, Outreach etc.
- Familiarity with customer data platforms like Segment or Hightouch, and analytics tools like Looker, Tableau, Omni — a natural fit with the dbt ecosystem.
- Exposure to newer GTM AI tooling such as Claude Code, Parallel, Unify, or Cursor.
- Experience designing or optimizing marketing attribution models, lead scoring, or conversion funnels.
- Experience in a product-led growth (PLG) or B2B SaaS environment.
Compensation
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 Lab’s total rewards during your interview process. In select locations (including Boston, Chicago, Denver, Los Angeles, Philadelphia, New York City, Austin, San Francisco, Washington, DC, and Seattle), an alternate range may apply, as specified below.
- The typical starting salary range for this role is:
- $155,000 - $200,000 USD
- The typical starting salary range for this role in the select locations listed is:
- $180,000 - $240,000 USD
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.
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