Currently tracking 3 active AI roles, down 43% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $180k–$250k (avg $214k).
Data AI · Data transformation
dbt Labs currently has 3 active AI-related roles in our index. The most common open titles are: Staff Software Engineer (2), Staff Product Manager- Developer Experience. Most positions are in Engineering and Product.
dbt Labs's active AI hiring is concentrated in: agents (100%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
dbt Labs is hiring AI talent in: India (2 roles), United States (1 role).
Job postings at dbt Labs most frequently reference: agent orchestration, agent research, tool use, llm observability, guardrails.
| Title | Stage | AI score |
|---|---|---|
| GTM Automation Engineer This role focuses on building and scaling an AI program for Go-to-Market (GTM) automation at dbt Labs. The engineer will design, implement, and deploy AI agents and capabilities to improve GTM productivity, automate tasks like account research and outreach, and drive revenue growth. The role involves full lifecycle ownership from identifying inefficiencies to shipping and iterating on AI solutions, using tools like Clay, Glean, Claude, and LLM APIs. | Agent | 7 |
| Staff Software Engineer Staff Software Engineer role focused on building autonomous and assisted agents that operate across the Analytics Development Life Cycle (ADLC). The agents will reason over enterprise context, act on data products, and improve the system over time through decision memory. Responsibilities include designing and implementing agents for various ADLC stages, orchestrating agent workflows, integrating with existing systems, and encoding governance policies. | Agent | 7 |
| Manager, Software Engineering Manager for the AI Platform Team, responsible for building the Agentic Platform that powers internal AI features and external AI integrations. The role involves architecting the "Agent-First" Experience, defining dbt MCP Strategy, and bridging platform and product for agentic use cases. Requires experience in people management, agentic architectures, APIs, and software engineering fundamentals in an AI context. | Agent | 7 |