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Member of Technical Staff

Catalog · San Francisco · On-site

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About Catalog

As data to be stored keeps growing, traditional infrastructure cannot scale indefinitely. DNA introduces a new storage media engineered for density, longevity & resource efficiency. Backed by NEA, SOSV and Techstars.

About the role

As a Member of Technical Staff, you will ship core systems, set engineering culture, and move the mission from prototype to platform. You will work across the stack and own problems end to end. If there appears to be a fit, we'll reach out to schedule 2-3 short technicals. After, we'll schedule an onsite in our office, where you'll work on a small project, discuss ideas, and meet the team.

What they're looking for

  • Have built zero to one products that users love and trust
  • Blend strong engineering with sharp product taste and data intuition
  • AI-native
  • Move fast, write clean code, and instrument everything
  • Want high ownership in a small, talent-dense team in San Francisco
More about this role

Catalog is building the commerce layer for AI - the missing infrastructure that lets agents not just search the web, but understand, reason about, and transact with products. We power the next generation of AI experiences that will reshape how people discover and buy online.

As a Member of Technical Staff, you will ship core systems, set engineering culture, and move the mission from prototype to platform. You will work across the stack and own problems end to end.

Have built zero to one products that users love and trust.

Blend strong engineering with sharp product taste and data intuition.

AI-native.

Move fast, write clean code, and instrument everything.

Want high ownership in a small, talent-dense team in San Francisco.

Design and ship agentic-search APIs that return structured, live product data in milliseconds.

Integrate checkout rails so agents can transact with any merchant.

Stand up an embeddings and retrieval layer that balances recall, precision, and cost.

Launch a product graph and ranking pipeline that learns from real outcomes.

Shipped data products in production.

Experience with recommendation systems or information retrieval.

Familiarity with developing APIs,...

Read the full posting on Catalog's site ↗

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