Member of Technical Staff - Atlas

Basis AI•New York, NY

3d•$100,000 - $300,000•Onsite

About The Position

Atlas is an internal team at Basis dedicated to finding the answer to what knowledge work looks like when we have AGI. 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.

Requirements

In person in Flatiron, NYC 5 days a week
Excited about working with coding agents (we give every engineer an unlimited token budget)
Excited about working at the frontier of applying agents to real economy problems
First principles and systems thinking.
Thinking beyond the engineering; understand the domain deeply: the data systems, the workflows, the work our agents are performing.
Ownership of outcomes.
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.

Responsibilities

Build intelligence deeper into workflows.
Ship agent teammates that push code directly to production.
Develop systems that keep company knowledge current automatically.
Create services that diagnose and repair themselves.
Invent new infrastructure, interfaces, operating models, and ways for humans and agents to work together.