Senior R&D Software Engineer, Fivetran AI
Senior R&D Software Engineer building the governed context layer (Agents Schema and Context Builder) for trustworthy AI agents. Research, prototype, and ship production full-stack features across backend, frontend, SRE, and QA in a fast-moving startup-like AI team.
About the job
What You’ll Do
- Research emerging techniques in retrieval, reasoning, and agentic AI, and evaluate what’s actually relevant to Fivetran 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 Fivetran 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 at scale
- Write and maintain tests, and do hands-on QA to 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 to shape what gets built next
- Develop software designs and contribute to the technical roadmap for the Fivetran AI platform
- Contribute to hiring by participating in the interview process
Skills We’re Looking For
- 5+ 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 in your subject area, capable of executing complex, ambiguous tasks with minimal hand-holding
- Comfortable reading AI/ML research and turning promising findings into working prototypes
- Strong product and market awareness — able to judge which emerging techniques are worth building versus which are hype
- 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
- Analytical mindset to identify gaps in existing systems and design practical, pragmatic improvements
- 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
Skills
Python, Java, SQL, dbt, LLMs, Vector Databases, BigQuery, Snowflake, Databricks, Mcp, React, TypeScript, Kubernetes, RAG, AWS
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