Senior R&D Software Engineer, Fivetran AI
$174,915–$209,907 year
HybridOakland, California, United States
Oakland, California, United StatesHybridPart Time$174,915–$209,907 yearSenior LevelTECHMedium
Part TimeSenior LevelMediumTECH
Job Summary
Research emerging AI retrieval and reasoning techniques, then prototype and ship production-grade features for the Fivetran AI platform. Build and maintain back-end and front-end systems, including Agents Schema pipelines and the Context Catalog UI, while contributing to AISQL capabilities that translate natural language to SQL. Take ownership of production reliability through on-call rotation, incident response, and SRE work, and write tests to perform hands-on QA. Partner with product teams to shape the technical roadmap and participate in the hiring process.
Required Qualifications
- 5+ years of programming experience across Python and/or Java
- 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
- ability 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
- Writes well-structured, performant code
- 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
- two days in the office each week
Desired Qualifications
- 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
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