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.
AnswerThis is a scientific discovery platform used by over 200,000 researchers that reduces weeks of manual research work to hours.
Instead of manually searching, reading, and organizing dozens of papers, researchers use AnswerThis to find the most relevant work, see how ideas are connected, and get comprehensive answers to complex scientific questions with line by line answers.
This allows them to map research gaps, analyze trends, and draft literature reviews far faster, all while building a searchable library of their own research materials.
Salary
$120,000 - $200,000
Equity
0.1% - 0.5%
Location
Remote
Experience
3+ years
Total raised
$500K
Last stage
Seed
Investors
No applications, no recruiter spam. Just the intro.
A few questions to make sure this role is the right shape for you. Two minutes.
I write the intro, send it to the founder, and handle the back-and-forth.
If they’re a yes, I book the chat. You show up — that’s the whole job-hunt.