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Trove AI

Founding Backend Engineer

Reposted 2 Days Ago
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In-Office
San Francisco, CA
175K-300K Annually
Mid level
In-Office
San Francisco, CA
175K-300K Annually
Mid level
As a Founding Backend Engineer at Trove, you will innovate GenAI applications, develop algorithms for knowledge graphs, and collaborate with AI labs and financial firms.
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About Trove

  • Trove is developing an AI associate for financial firms - think enterprise search & agents for private equity, hedge funds, and banks

  • Our mission is to deliver associate‑level AGI

  • We’ve raised nearly $10M from Menlo and Khosla Ventures

  • We have strong initial traction - large enterprise contracts and user engagement on par with best-in-class B2B AI applications

Why this role?

  • High impact: You’ll shape the product and culture from day one. Expect to dive into unsolved challenges at the Gen AI application frontier – enterprise‑scale data retrieval, autonomous agents, and knowledge graphs.

  • High equity: 0.5%+ equity. $175K - 300K cash. You will own a meaningful piece of the company.

  • High talent density: Be a part of a great founding team in SF.

    • Shivaal Roy (CTO) was a founding engineer at Glean ($100M+ ARR today) and managed the Assistant and Search teams, where he solved similar problems.

    • Danny Goldman (CEO) was a top performer at Bain’s Private Equity group

What you’ll do

  • Push the frontier of GenAI applications by delivering human-level capabilities

  • Design and build novel knowledge graphs algorithms to power search and retrieval over unstructured and structured firm data

  • Collaborate with the top AI labs and elite financial firms to design reliable AI-native systems

Who you are

  • Track record of extraordinary ability

  • 3 - 8 years of software engineering experience

  • Excitement to work in person 4 days a week in SF

  • Nice but not required: experience with LLMs, search and retrieval, previous work at a financial firm

Top Skills

AI
Algorithms
Genai
Knowledge Graphs
Structured Data
Unstructured Data

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