Software Engineer

interface.ai•San Francisco, CA

7h•$135,000 - $175,000•Onsite

About The Position

We're rebuilding interface.ai as an AI-native company — and we want engineers who learn to work this way from day one, not after unlearning somewhere else's habits. As an early-career Software Engineer, you ship production features from your first weeks — real users, real money, real stakes — and take on larger scope as fast as you can carry it. This is not a rotational program, and you won't be one of a cohort. We hire early-career engineers in ones and twos. Our product and engineering org is deliberately lean relative to the millions of conversations it serves — new engineers get real scope because there's no one else queued up for it. Agents take the routine work; you spend your time on decisions and on the evaluation harnesses that prove what shipped is correct. We build in person, from San Francisco. At our stage speed is the whole game, and the fastest path between a problem and a decision is two engineers at the same desk. Scope, title, and pay track what you've put into production — the expected path is owning bounded pieces of the product end-to-end within your first year.

Requirements

You build things nobody asked you to build — a side project with actual users, hackathon wins, merged open-source PRs, or internship work that shipped.
You've built with LLMs and you verify their output instead of trusting it.
A degree in CS or a related field (engineering, math, physics, statistics) — or show us what you've built instead.
High agency — you'd rather be handed a problem than a ticket, and you close loops without reminders.
Graduating 2024 – December 2026, or up to ~2 years of experience.
On-site in downtown San Francisco office 5 days a week.

Nice To Haves

Competitive programming (Codeforces, ICPC, USACO)
Experience in fintech or banking infrastructure

Responsibilities

Ship production features from your first weeks — real users, real money, real stakes.
Take on larger scope as fast as you can carry it.
Own the evals for what you build.
Build with LLMs daily — steering agents through the routine work so your time goes where judgment matters.
Own bounded pieces of the product end-to-end within your first year.