About Spring
Spring is an AI-native lender. We spent the first eight months of our business building completely novel in-house software — loan management systems, payment rails infrastructure, and technology for analyzing business bank transactions and financials. That foundation let us originate over $100 million in funding to CPG brands within our first year of business.
Now we're building the product that all of that infrastructure was designed to power: an AI CFO agent. The addressable market starts with tens of thousands of CPG brands and extends to small businesses across many verticals. Our lending operation gives us a unique advantage — deep financial data, direct customer relationships, and the real-world workflows that the agent needs to automate.
The CFO agent operates across a brand's entire financial stack — managing deductions, handling email workflows, working with accounting and banking data, and more. These are the kinds of tasks that consume hours of a finance team's week and are perfectly suited to agentic automation.
The interface itself is a core part of the product. The agent renders an opinionated, flexible UI that mutates in real time — displaying actions, visualizations, and interactable elements through LLM tool calls. It's a true copilot: the agent acts, the user sees what it's doing, and either of them can drive what happens next.
What We're Building
Our CFO agent is inspired by the architecture of tools like Claude Code — a system that uses its own outputs to continuously improve. We're applying modern machine learning techniques to create a self-improving flywheel: the agent upgrades its own skills and abilities over time based on real user interactions and outcomes.
The stack is TypeScript on the frontend and Python on the backend. If you've used agentic coding tools in your own workflow, you'll immediately recognize what we're doing — and you'll have strong opinions about how to make it better. That's exactly what we want.
Who We're Looking For
We're a team of nine, including two developers. We don't have a dedicated product person. That means whoever joins will have an outsized impact on what gets built and how.
We're open to several profiles:
- Engineers with product instincts— you care about what you're building, not just how it's built. You have opinions about UX, can talk to customers, and make design decisions without waiting for a spec.
- Backend engineers— you're strong in Python and want to work on the ML-driven systems that power the agent's learning loop.
- Product managers who can build— you've shipped software, you understand technical tradeoffs, and you want to own a product from zero to one.
What matters most:
- You're self-motivated and want to work on something novel
- You're excited about agentic AI and understand why it's different from traditional software
- You want to be early at a company where your work defines the product
Details
- Location: In-person in New York City
- Remote: For strong candidates outside New York, we're open to flexible paid trial periods to test the fit before relocating
- Compensation: Equity + competitive compensation (discussed during the process)