Senior Staff R&d Software Engineer, Fivetran AI

Fivetran Fivetran · Data AI · Oakland, CA · Fivetran AI Department

Senior Staff R&D Software Engineer for Fivetran AI, focusing on building the governed context layer for AI agents. This role involves researching emerging AI techniques, prototyping, and shipping production software, including agent-ready context storage (Agents Schema) and a managed service (Context Builder). The engineer will define technical direction, build back-end and front-end systems, and ensure production reliability for AI products like AISQL. The role requires a generalist approach, operating with high independence in a startup-like environment within Fivetran.

What you'd actually do

  1. Identify which emerging AI research and techniques are worth pursuing, and set the agenda for Fivetran AI’s technical roadmap accordingly
  2. Prototype new ideas quickly, then take the ones that prove out and turn them into shipped, production-grade features
  3. Define technical direction that spans Fivetran AI and collaborating departments — product, data platform, and go-to-market — resolving architectural tradeoffs that cross department lines
  4. Build and maintain both back-end and front-end systems for the Fivetran AI product — from Agents Schema pipelines to the Context Catalog UI
  5. Set the long-term technical vision for capabilities like AISQL: natural language to SQL grounded in dbt metric definitions, executed natively against the warehouse

Skills

Required

  • Python
  • Java
  • SQL
  • dbt
  • LLMs (Claude, ChatGPT, Gemini)
  • vector databases
  • BigQuery / Snowflake / Databricks
  • Kubernetes
  • research emerging techniques
  • prototyping
  • production software development
  • backend systems
  • front-end systems
  • technical direction
  • architectural tradeoffs
  • production reliability
  • on-call rotation
  • incident response
  • SRE work
  • engineering quality
  • testing
  • QA practices
  • coding agents

Nice to have

  • React
  • TypeScript
  • MCP protocol

What the JD emphasized

  • research emerging techniques
  • ship it as production software
  • prototyping
  • retrieval technique
  • backend service
  • SRE or QA work
  • define your own direction
  • execute with the highest level of independence
  • thrive on that range and ambiguity
  • governed context layer
  • Agents Schema
  • Context Builder
  • AISQL

Other signals

  • building the governed context layer that solves this problem
  • Agents Schema, an open standard for storing agent-ready context
  • Context Builder, the managed service that keeps it filled and fresh
  • research emerging techniques in the fast-moving AI landscape
  • ship it as production software
  • prototyping a new retrieval technique
  • hardening a backend service
  • AISQL: natural language to SQL grounded in dbt metric definitions