Senior R&d Software Engineer, Fivetran AI

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

Senior R&D Software Engineer for Fivetran AI team, focused on building a governed context layer for AI agents. The role involves researching emerging AI techniques, prototyping, shipping production software, and contributing to both backend and frontend systems. Emphasis on building infrastructure agents can trust, embracing open standards, and scaling efficiently. Requires strong programming experience and ability to work across the full stack.

What you'd actually do

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

Skills

Required

  • 5+ years of programming experience across Python and/or Java
  • Ability to move fluidly between back-end and front-end work
  • Comfortable reading AI/ML research and turning promising findings into production software

Nice to have

  • Experience with vector databases
  • Experience with BigQuery / Snowflake / Databricks
  • Experience with Kubernetes

What the JD emphasized

  • agents are the new primary data consumers
  • fundamentally different requirements
  • explicitly codified, governed, and traceable
  • governed context layer
  • open standard for storing agent-ready context
  • managed service that keeps it filled and fresh
  • research emerging techniques
  • bring real product and market understanding
  • ship it as production software
  • true generalist
  • wear whatever hat the moment calls for
  • prototyping a new retrieval technique
  • hardening a backend service
  • SRE or QA work
  • operates like a startup
  • thrive on that range rather than staying in one lane
  • Builds Infrastructure Agents Can Trust
  • governed context layer that AI agents depend on
  • traceable lineage
  • data contracts
  • auditable history
  • Embraces Open Standards
  • portable, interoperable data infrastructure
  • Scales Without Breaking
  • efficient at agent scale
  • context retrieval is fast, accurate, and cost-controlled
  • no-nonsense tools
  • simplicity and effectiveness
  • back-end is built on Java, Python, Postgres, and Kubernetes
  • front-end is built on React and TypeScript
  • Research emerging techniques in retrieval, reasoning, and agentic AI
  • evaluate what’s actually relevant
  • Prototype new ideas quickly
  • turn them into shipped, production-grade features
  • Build and maintain both back-end and front-end systems
  • Agents Schema pipelines
  • Context Catalog UI
  • AISQL capability
  • natural language to SQL grounded in dbt metric definitions
  • executed natively against the warehouse
  • ownership of production reliability
  • on-call rotation
  • incident response
  • SRE work
  • keep the platform trustworthy at scale
  • Write and maintain tests
  • hands-on QA
  • catch issues before customers do
  • Use coding agents to automate the repetitive parts of the job
  • freeing up time for the research and design work that needs a human
  • Partner with product and design
  • bringing your own understanding of the AI tooling market
  • shape what gets built next
  • Develop software designs
  • contribute to the technical roadmap
  • Fivetran AI platform
  • Contribute to hiring
  • participating in the interview process
  • 5+ years of programming experience
  • Python and/or Java
  • move fluidly between back-end and front-end work
  • Considered a trusted expert
  • capable of executing complex, ambiguous tasks
  • minimal hand-holding
  • Comfortable reading AI/ML research
  • turning promising findings into production software

Other signals

  • building AI agents
  • governed context layer
  • agent-ready context
  • retrieval, reasoning, and agentic AI