Finance Generalist

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.

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

Most finance roles inherit a business model. This one helps build one.

Our agents do work that accounting firms have always staffed with people. That makes the questions finance owns at Basis the questions that decide whether the company works: how you price hours of autonomous work, what margins look like when compute is a real cost of revenue, how far ahead of demand you build capacity, and where the next dollar of a fundraise should go.

There is no playbook for this yet. You’ll help write it.

If you’ve spent years in banking, private equity, or venture modeling businesses like this from the outside, this is the chance to do it from the inside, with the data, the operators, and the ability to change the answer.

• Own the models the company runs on. Revenue, headcount, unit economics, cash. Leadership makes decisions off your work, so it has to be right and it has to be legible.
• Take analysis to action. Evaluating a pricing change or a new investment is half the job. The other half is getting the right people aligned and making sure the decision actually gets implemented. You follow the number until something changes because of it.
• Chase down what doesn’t add up. When a metric moves and the explanation doesn’t sniff right, you go deep enough to find out why, whether that’s the data, the contract, or the Slack thread, and you come back with a real answer.
• Rebuild finance around AI. You’ll run experiments on where LLMs can take on finance work: the recurring reconciliation, the variance commentary, the board deck refresh. When you catch yourself doing a process by hand, you’ll ask whether you can build a skill, an agent, or a workflow that moves you from doing the work to reviewing it. Then you’ll build it.
• Be the finance team for the whole company. Field a founder’s question on runway and an engineer’s question on how commissions work with the same care. Deliver a brief to the leadership team on Monday; help a GTM lead read a capacity model on Tuesday.

NYC, Flatiron office. In-person team, five days a week.

• An operator, not just an analyst. You’ve watched good analysis go nowhere and it bothers you. You measure your work by what changed, not by what got produced.
• Hyper curious. You ask why until you get an answer that holds up. You have a nose for when something is off and the patience to trace it to the source, and you use what you find to make better decisions.
• AI-forward. You already use AI to work faster and go deeper, and you want to know how far it can go. You’d rather run the experiment than read about it. You’re excited by the…