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AI Education Lead

Job in New York, New York County, New York, 10261, USA
Listing for: getbasis.ai
Full Time position
Listed on 2026-07-29
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 190000 USD Yearly USD 120000.00 190000.00 YEAR
Job Description & How to Apply Below
Location: New York

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 as 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.

About the Role

As our AI Education Lead, your full-time job is to make every person at Basis maximally effective at using AI.

This is not an introductory AI training role. People at Basis already use AI deeply in their work, and many build with agents every day. You will not spend your time explaining what an agent is or teaching people to write their first prompt. Your job is to keep an already AI-native organization at the cutting edge as models and tools change every week—and to help each person develop the judgment to redesign their own work around them.

To lead at that level, you must live at the frontier yourself. When a major model ships, you should be among the first to test it, build with it, and form a view on what actually changed. You run multiple agents, build your own workflows, understand how models behave, and can separate a compelling demo from a durable capability. Your teaching comes from firsthand practice.

You will turn that expertise into the system through which Basis learns. That might mean designing company-wide programs, creating role-specific playbooks, leading hands-on workshops, sitting beside one teammate until a new workflow clicks, or building skills and agents that teach people in the flow of work. You must make complex concepts intuitive without flattening them and explain subtle distinctions across models, tools, and workflows to engineers and non-engineers alike.

You own adoption, not attendance. Success means people work differently, agents take…

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