Senior Data & AI Platform Engineer, AWS, Snowflake, Vector Search

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🕒 February 25

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RevenueBase

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

🤝 B2B

☁️ SaaS

🔌 API

💰 $6M Seed Round - RevenueBase on 2022-04

B2B • SaaS • API

RevenueBase is a data infrastructure company for B2B go-to-market products that provides continuously refreshed company and contact data, APIs, and data tools (including email verification) to power marketing, sales, and ops teams. It offers verified, living B2B data and actionable insights to improve outreach, increase conversion rates, reduce bounce rates, and maintain data quality for GTM platforms and AI-driven workflows.

📋 Description

• 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

🎯 Requirements

• 5+ years of software engineering experience • Strong backend engineering skills (Python preferred; other modern languages acceptable) • Solid experience with: • AWS (IAM, Lambda, ECS/EKS, S3, networking, security best practices) • Data warehousing (Snowflake preferred) • API design and distributed systems • Hands-on experience working with LLM APIs (e.g., OpenAI) and embedding workflows • Experience with vector databases (Pinecone or similar) • Strong understanding of data modeling, ETL/ELT patterns, and performance optimization • Production experience in at least one startup environment • Ability to operate independently and ship high-impact systems end-to-end

🏖️ Benefits

• Work on practical, production-grade AI systems • Direct impact on how data is leveraged across the company • Startup speed with real ownership and autonomy • Opportunity to define the internal AI platform from the ground up