Sr. Principal AI Systems Architect

About this role

From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven.

About Us

Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

About the Role

Fivetran needs an engineer-architect who can make the AI analyst experience real, dependable, and extensible. This role owns the architecture behind the analyst AI system, including metadata contracts, tool interfaces, context assembly, prompt and skill orchestration, evaluation loops, and the operational patterns that make agents useful in real workflows instead of isolated demos.

This is a systems role as much as an AI role. The challenge is not just getting an LLM to do something impressive once. The challenge is building a product-quality analyst system that can reason over schema and business context, use tools correctly, recover from ambiguity, and improve through disciplined evaluation and iteration.

This is a full-time, hybrid position based at our Oakland, CA office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team.

What You'll Do

• Define the architecture for the analyst AI stack across prompts, tools, metadata, memory and context strategies, evaluation, and runtime safety.

• Build the abstractions and interfaces that allow product teams to add new agent capabilities without creating brittle prompt sprawl.

• Design retrieval and context strategies that give the model the right information at the right time with strong cost, latency, and quality tradeoffs.

• Establish evaluation loops, benchmark suites, and review processes so model behavior can be measured, debugged, and improved systematically.

• Partner with product, engineering, and analyst-domain experts to translate real analytical workflows into robust AI-assisted product capabilities.

• Drive quality standards around correctness, trust, transparency, and failure handling in analyst-facing AI experiences.

What We're Looking For

• Deep experience building AI-enabled product systems, not just running experiments.

• Strong software architecture skills, especially around APIs, contracts, orchestration, and system boundaries.

• Practical understanding of LLM prompting, tool use, retrieval, structured outputs, and evaluation methods.

• Ability to work fluently across backend engineering, product constraints, and user workflow design.

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