AnswerThis

Who we are Trillions of dollars flow into global R&D every year, and a massive share of it goes to researchers manually reading papers, writing literature reviews, and assembling evidence packages. This is the work that decides whether a new drug or medical device reaches patients, and almost all of it is still done by hand. AnswerThis is building the operating system for scientific knowledge inside enterprises. Our agents search, synthesize, and draft evidence-based research autonomously. We have 200K+ researchers on the platform across universities and Fortune 500 companies, and we're going deep into life sciences, where the workflows are most manual and the stakes are highest. We're YC-backed, growing fast, and small on purpose. What we're solving Existing research is still hard to search. Semantic search has improved things, but finding the right evidence across fragmented sources remains a massive unsolved problem. Research can't update itself. A literature review is a snapshot. But the underlying data, internal trial results, competitive intelligence, new publications, all of it changes constantly. Nobody has a good answer for keeping research current. Drafting research is painful. Scientists spend months creating static, one-time documents that never update, are impossible to search, and decay the day they're published. We're building the system that makes research a living, compounding asset instead of a disposable artifact. Who we're looking for You're a senior engineer who has built AI agent systems in production and led teams or projects at startups. You've shipped under uncertainty, without specs, on timelines that didn't make sense on paper. You'll own the technical architecture and velocity of the product. That means prioritizing, implementing, and owning features end to end, from customer problem to deployed solution. You'll work directly with enterprise customers, make hard calls on scope and sequencing with limited information, and measure success by whether the product grows revenue. You'll also help us build the engineering team over time. You know what works at 3 engineers breaks at 10, and you want to design how that transition happens. This role is in-person in San Francisco. If you've only operated inside large engineering orgs with established processes, or if you optimize for technical elegance over business impact, this isn't the right fit. Compensation $170-240K+ base salary with meaningful equity in a YC-backed company at $1.5M+ ARR.

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 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.