Job description

We crossed $1M ARR in 8 months. 200,000+ researchers at Stanford, MIT, and Amazon use us to do literature reviews 10x faster.\ \ Now we're building something bigger: the system of record for scientists where they can find papers, analyze experiments, and write their drafts while collaborating with other scientists as well as our AI agents. \ \ You should apply if you:\ \ → Ship fast and learn faster \ → Know the agentic AI stack cold (vector DBs, graph RAG, agent memory) \ → Have built full-stack products that scaled past 1M users \ → Actually care about accelerating scientific discovery\ \ Bonus: You've published research yourself. \ \ Don't apply if you:\ \ → Can't be in SF, in person \ → Haven't used the product yet \ → Don't want to talk to customers \ \ $120K-$200K + equity. We're a small team backed by YC. \ \ Reach out on careers \[at\] [answerthis.io](http://answerthis.io)\ \ Tell us what you hate about AnswerThis, what you love, and one project you're proud of alongside your resume.\ \ Science moves too slowly. Help us fix that.

AI agent orchestration

AI agent orchestration · AnswerThis

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