Location: San Francisco, CA
Role Type: Full-time, Individual Contributor
About Us
Sage Labs is redefining product discovery with AI-driven search and personalization. We operate at the intersection of machine learning, distributed systems, and high-performance computing, tackling some of commerce’s toughest engineering challenges.
We have a flat structure that prioritizes execution over hierarchy. As a Data Engineer you’ll design and build the core data infrastructure powering our platform, ensuring seamless data flow at scale.
Your Impact•Architect and maintain ETL pipelines to ingest and process third-party data
•Build real-time and batch pipelines that power AI-driven search, recommendations, and personalization
•Optimize storage, retrieval, and performance for AI models
•Enhance data lineage, observability, and governance
•Partner with AI engineers and backend teams to optimize data flows
Who You Are
•8+ years in data engineering, infrastructure, or backend systems
•Scaled data systems from 0 to 1, including data catalogs and metadata management
•Hands-on with Kafka, Flink, Beam, or Spark
•Proficient in BigQuery, Snowflake, or Redshift or other real-time toolkits
•Strong SQL, Python, and distributed systems background
•Familiarity with vector databases and AI-powered data pipelines
Why Join Us?
•This is a high-impact, high-ownership role where you'll own a lot
•Work alongside AI experts and startup veterans
•Rare opportunity to shape data systems in a 0-to-1 environment
•Competitive compensation & equity—We’re in this for the long haul
If you're passionate about designing scalable data systems for AI-driven applications, we want to hear from you
Apply now or reach out to build@sagelabs.ai
No recruiters or agencies please
Benefits Include