About the role
RevenueBase: We're building the data infrastructure that makes AI agents trustworthy instead of error-prone. We provide continuously refreshed, verified B2B data for autonomous AI agents and GTM workflows. We've tripled growth while maintaining 100% gross dollar retention and staying cashflow positive. We power AI agents for Clay, Zoominfo, Dun & Bradstreet, and the next generation of AI GTM tools.
About
the Role We are looking for a Senior Data & AI Platform Engineer to build internal tools and services on top of our large-scale data infrastructure. Your primary focus will be developing systems that leverage vector embeddings, LLM APIs, and semantic search to unlock value from structured and unstructured data. This is a hands-on engineering role for someone who enjoys building practical AI-powered tools — not just experiments — and shipping them into production in a fast-moving startup environment. What You’ll Do Design and build data-driven tools that operate on large datasets stored in S3 and Snowflake Implement pipelines that: Extract specific columns or datasets from Snowflake Generate vector embeddings via APIs such as OpenAI Store and manage embeddings in vector databases like Pinecone Enable semantic search and similarity-based retrieval Develop enrichment workflows that: Query structured data Use LLM APIs to generate new derived columns Write enriched results back into Snowflake Build reusable internal services and SDKs around embedding generation, prompt orchestration, and data augmentation Optimize performance and cost across AWS infrastructure Work closely with product and data teams to turn use cases into scalable engineering solutions Ensure reliability, observability, and maintainability of AI-powered pipelines Example Projects Tool to extract a single Snowflake column, generate embeddings, push to Pinecone, and expose a semantic search API Batch enrichment pipeline that queries records from Snowflake, calls OpenAI APIs for structured enrichment, and writes new columns back Internal framework for LLM-based data transformation and validation Query abstraction layer to make AI-enhanced analytics accessible to non-engineering teams Required