# Staff R&D Software Engineer, Fivetran AI

**Company:** [Fivetran](https://hotfix.jobs/companies/fivetran)
**Location:** Denver, CO, New York, NY, Austin, TX, Oakland, CA
**Role:** ML Engineering
**Salary:** $196k – $245k/yr
**Experience:** 8+ years
**Skills:** Python, Java, SQL, dbt, LLMs, RAG, Vector Databases, BigQuery, Snowflake, Databricks, mcp, React, TypeScript, Kubernetes
**Posted:** 2026-07-21

> Staff R&D Software Engineer building the governed context layer (Agents Schema and Context Builder) for trustworthy AI agents. Research AI techniques, prototype and ship production backend/frontend features, own reliability/SRE/QA, define technical direction across teams, and mentor others in a fast-moving startup-like environment.

## Job Description

## What You’ll Do
- Research emerging techniques in retrieval, reasoning, and agentic AI, and decide what’s actually worth pursuing for Fivetran AI’s roadmap — then convince others
- Prototype new ideas quickly, then take the ones that prove out and turn them into shipped, production-grade features
- Define technical direction that spans multiple teams within Fivetran AI, ensuring architecture decisions made in one area don’t create problems in another
- Build and maintain both back-end and front-end systems for the Fivetran AI product — from Agents Schema pipelines to the Context Catalog UI
- Drive the AISQL capability forward: natural language to SQL grounded in dbt metric definitions, executed natively against the warehouse
- Take ownership of production reliability across the platform: on-call rotation, incident response, and SRE work to keep the system trustworthy at scale
- Set the bar for testing and QA practices, and do hands-on QA work yourself when it matters most
- Use coding agents to automate the repetitive parts of the job, freeing up time for the research and design work that needs a human
- Take high-level direction from product and leadership and independently define and execute the concrete plan to get there
- Mentor other engineers and raise the technical bar across the Fivetran AI team
- Contribute to hiring by participating in and helping shape the interview process

## Skills We’re Looking For
- 8+ years of programming experience across Python and/or Java, with the ability to move fluidly between back-end and front-end work
- Considered a trusted expert beyond your own team, able to exert influence and define technical direction across multiple teams
- Comfortable reading AI/ML research and turning promising findings into working prototypes, then production systems
- Strong product and market awareness — able to judge which emerging techniques are worth building versus which are hype
- Track record of taking ambiguous, high-level direction and independently defining and executing the concrete work to deliver it
- Experience with SQL and data warehouses (BigQuery, Snowflake, Databricks, or similar)
- Genuine willingness to work across the full stack: research, backend, frontend, SRE, and QA, as the team’s needs demand
- Writes well-structured, performant code and can dive into unfamiliar codebases to suggest improvements
- Experience using coding agents or similar AI tooling to speed up day-to-day engineering work
- Demonstrated ability to mentor other engineers and influence technical decisions beyond your immediate team
- Thrives in a startup-like environment with shifting priorities and a high degree of ownership

## Bonus Skills
- Experience with LLM-powered applications — RAG pipelines, embeddings, evaluation frameworks, or agent frameworks
- Familiarity with semantic layers — dbt, LookML, Sigma, or similar
- Experience with the MCP (Model Context Protocol) ecosystem or building AI agent integrations
- Background in site reliability engineering — monitoring, alerting, incident response
- Experience in data processing (ETL, ELT) and/or building data connectors
- Experienced working in a cloud environment utilizing AWS, GCP, Kubernetes, or Docker
- Contributions to open source AI or data projects

## Technologies You’ll Use
- Python, Java, SQL, dbt, LLMs (Claude, ChatGPT, Gemini), vector databases, BigQuery / Snowflake / Databricks, MCP protocol, React, TypeScript, Kubernetes

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