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.
175k – 210k/yr
Hybrid5+ YOEML Engineering
About the role
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
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