Senior R&D Software Engineer, Fivetran AI

United States Digital Space LLC; Denver (CO); Hybrid; USD 120,000 - 180,000; Full time

Job summary

United States Digital Space LLC is seeking a Senior R&D Software Engineer to join our fast-growing AI team. Your data stack was built for humans — but agents are the new primary data consumers, and they have fundamentally different requirements.

Agents can’t intuit context; it must be explicitly codified, governed, and traceable. We’re building the governed context layer that solves this problem: Agents Schema, an open standard for storing agent-ready context in the customer data warehouse, and

Qualifications

• Experience in AI/ML system development and production features.
• Ability to prototype quickly and ship production-grade software.
• Experience building backend and frontend systems for AI products.
• On-call rotation and site reliability engineering responsibilities.
• Contributes to AI/SQL capabilities and data infrastructure.

Responsibilities

• Research retrieval techniques and evaluate relevance to the roadmap.
• Prototype ideas quickly and turn them into shipped features.
• Build and maintain backend and frontend systems for the AI product.
• Contribute to AISQL capability: NL to SQL in the warehouse.
• Own production reliability and incident response.

Skills

Software engineering

Research

Prototype development

SRE & incident response

Cross-functional collaboration

Tools

Python

Java

SQL

dbt

React

TypeScript

Kubernetes

BigQuery

Snowflake

Databricks

Iceberg

Delta Lake

MCP protocol

LLMs

Vector databases

Job description

About Us

from the company’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With the company, 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.

the company 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. the company 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 the company and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites.

About the Role

the company and dbt are building the open data infrastructure that powers AI agents you can trust.

the company is looking for a Senior R&D Software Engineer to join our fast-growing the company AI team. Your data stack was built for humans — but agents are the new primary data consumers, and they have fundamentally different requirements. Agents can’t intuit context; it must be explicitly codified, governed, and traceable. We’re building the governed context layer that solves this problem: Agents Schema, an open standard for storing agent-ready context directly in the customer’s own data warehouse, and Context Builder, the managed service that keeps it filled and fresh.

This role goes well beyond standard engineering. You’ll research emerging techniques in the fast-moving AI landscape and bring real product and market understanding to decide which ideas are worth pursuing — and then you’ll take what you’ve learned and ship it as production software. We’re looking for a true generalist who is willing and able to wear whatever hat the moment calls for: prototyping a new retrieval technique one week, hardening a backend service the next, then doing SRE or QA work when the team needs it. the company AI operates like a startup within the company, and we need engineers who thrive on that range rather than staying in one lane.

the company is the epitome of data-driven development — our engineering team is focused on building a world class product that:

• Builds Infrastructure Agents Can Trust — join our mission to deliver the governed context layer that AI agents depend on: accurate semantic definitions, traceable lineage, data contracts, and auditable history baked in from the start.
• Embraces Open Standards — help build portable, interoperable data infrastructure: Agents Schema, open formats (Iceberg, Delta Lake), MCP-native interfaces, and connector skills that work with any model and any compute.
• Scales Without Breaking — work to make the company AI efficient at agent scale, where unit costs deflate as volume grows and context retrieval is fast, accurate, and cost-controlled.

We emphasize using no-nonsense tools and take great pride in the simplicity and effectiveness of the systems we build. Our back-end is built on Java, Python, Postgres, and Kubernetes, and our front-end is built on React and TypeScript.

This is a full-time hybrid position based out of our Denver, CO 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.

Technologies You’ll Use

Python, Java, SQL, dbt, LLMs (Claude, ChatGPT, Gemini), vector databases, BigQuery / Snowflake / Databricks, MCP protocol, React, TypeScript, Kubernetes

What You’ll Do

• Research emerging techniques in retrieval, reasoning, and agentic AI, and evaluate what’s actually relevant to the company AI’s roadmap
• Prototype new ideas quickly, then take the ones that prove out and turn them into shipped, production-grade features
• Build and maintain both back-end and front-end systems for the the company AI product — from Agents Schema pipelines to the Context Catalog UI
• Contribute to the AISQL capability: natural language to SQL grounded in dbt metric definitions, executed natively against the warehouse
• Take ownership of production reliability: on-call rotation, incident response, and SRE work to keep the platform trustworthy