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Member of Technical Staff - Atlas

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Basis AI New York, New York Office Source published Sep 20, 2026 Verified 13 hours ago
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Member of Technical Staff - Atlas
EmploymentFull-time

Overview

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Full job description

[https://app.ashbyhq.com/api/images/user-content/a3ff9955-736e-4a64-a923-c3c42b253641/17b03131-be3b-4bb8-9ad9-dbafd99fd465/image.png] ABOUT BASIS Basis builds real agents that do real work in the real economy. Our agents operate for hours at a time, performing end-to-end work for some of the largest accounting firms in the world. We recently raised $100M at >$1B valuation and are racing to deploy the most advanced applied ML at production scale. Our investors include: Khosla Ventures (Keith Rabois & Vinod Khosla), Accel (Miles Clements), Google Ventures, Nat Friedman & Daniel Gross, Adam D'Angelo, Jeff Dean, Jack Altman, Noam Brown, Kyle Vogt, Amjad Masad, Clem Delangue and many other operators/technical leaders. "Basis is on the frontier of building production-grade, long-horizon agents. They've pushed the limits of what we thought our models could do on real-world, economically valuable, complex accounting tasks. They've been a great collaborator in helping us shape what the future of agents looks like." — Prashant Mital, Applied AI Lead, OpenAI ABOUT ATLAS What does knowledge work look like when we have AGI? Atlas is an internal team at Basis dedicated to finding the answer. We’re a group of builders, former founders, and engineers that embed directly within our teams, so we can build intelligence deeper into their workflows. As models continue to improve, they change how companies are built and how teams operate. Basis is building the first AI-native company at scale. Atlas is responsible for making that possible. We’ve already shipped agent teammates that push code directly to production, systems that keep company knowledge current automatically, and services that diagnose and repair themselves. These systems do real work inside Basis today. Every advance in model capability opens another set of questions about how work should be organized and another set of things we can build. Our ambition is much larger than making each person 10% more productive. We’re building zero-human loops that handle entire jobs end-to-end and free up our team to take on higher level work. Getting there means inventing new infrastructure, interfaces, operating models, and ways for humans and agents to work together. Atlas began when Basis had fewer than forty people. Since then, Basis has raised $100M. Atlas has the resources, access, and mandate to pursue this seriously. Basis intends to grow at extraordinary speed, and doing so requires a fundamentally different operating model—one in which agents take on an increasing share of the work. There is no established playbook for that. Building it is our job. If “What is the future of knowledge work?” is the question you most want to spend the next several years answering—and you want to make the answer real at a fast-growing company—reach out. The kind of engineer who does well here We hire individuals, not resumes. Given how fast things are changing, it's more important to hire the best people than to hire the person with specific experience. First principles and systems thinking. Many of the problems we solve are net new. There's no playbook. We want people who can decompose a novel problem, reason from fundamentals rather than pattern match, and design things that compound. Thinking beyond the engineering. The engineers who do best here understand the domain deeply: the data systems, the workflows, the work our agents are performing. That understanding is what lets you design better systems, train better agents, and make better product decisions. Ownership of outcomes. Every project at Basis has a single Responsible Party (RP) who is accountable for whether it ships and whether it works. There are always more things to own than people to own them. Engineers own their own work at Basis. Read more about our RP system here Agency. Having the initiative to pick up the context you need to make good decisions. Talking to the right people, reading the data, understanding the problem deeply enough to know what matters. NON-NEGOTIABLES:

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