Member of the Technical Staff — Applied AI, Fullstack

About Stuut

Stuut is the AI coworker that runs order-to-cash for the world’s leading enterprises. Across order management, credit, collections, payments, cash application, disputes and deductions, Stuut does the work end to end and keeps going until the cash hits the bank.

Over 150 companies, spanning the mid-market to the Fortune 50, including Honeywell, ZoomInfo and PerkinElmer, use Stuut to unlock up to 40% more cash flow and cut DSO by 47%. More than $3 billion has moved through the platform to date.

Founded in New York by Tarek Alaruri and Ben Winter, Stuut has raised $93 million from Insight Partners, Andreessen Horowitz, M12, Microsoft’s Venture Fund, and others. Learn more at stuut.ai.

The Role

At Stuut, you'll build AI agents that do real order-to-cash work: collecting overdue invoices, responding to customer emails about invoices and payments, applying cash, and resolving disputes and deductions. You'll build the agents, their harnesses, and the product that makes them reliable in production.

Every customer has different processes, policies, and rules. Our agents adapt to how customers work, not the other way around. They need to use tools, manage long-running tasks, recover from failures, check their own work, and know when to involve a person.

Agent experience is a plus, not a requirement. If you've built reliable workflow or distributed systems, you already understand many of the hard problems: state, retries, and human handoffs. You can learn Pydantic AI and order-to-cash on the job.

What You'll Do

• Build agents that take receivables work from start to finish: applying payments, chasing overdue invoices and resolving deductions.
• Build the agent harness: the tools, structured outputs, guardrails and human approvals that decide when an agent acts, waits or escalates.
• Make every agent action traceable, and every write to a customer's ERP safe to retry and easy to review.
• Build the product, from APIs and data models to the UI, where finance teams set rules, review decisions and steer agents.
• Write evals against real customer outcomes, and turn each failure into a fix in the harness.
• Work with customers to learn how AR teams actually work, and turn their edge cases into better agents.
• You Might Be a Fit If You…
• Have built an agent that calls tools and takes real actions, at work or on your own.
• Ask "how would we know if this is wrong?" before you ship, and answer it with evals and traces.
• Have handled long-running agent work: state, retries, and runs that pause for a person and resume.
• Want to work where a wrong action costs a customer real money, and design for that.
• Like learning a new domain from the people who do the work. No finance background required.
• Big Plus
• Pydantic AI: Understand the framework and its approach to building agents, managing dependencies, using tools, and producing structured outputs.
• Product judgment: Can understand a customer's problem, identify what actually matters, and turn complex business workflows into simple, useful product capabilities.
• Customer-driven engineering.
• You like getting close to real workflows, finding the problems that matter, and turning them into simple, useful products.
• US Compensation
• Top-of-market salary and equity package