Member of Technical Staff - Full Stack, Credit

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

We’re hiring a Member of Technical Staff – Full Stack, Credit to help build Stuut’s next generation of credit products, including trade credit, receivables financing, payment plans, and related financial workflows.

You’ll work closely with product, data, and operations to turn messy operational and financial data into trustworthy credit state and deterministic decisions. You’ll build systems that understand what is owed, what has been paid, what is disputed, what counts toward exposure, and how those facts should drive credit policy.

This is a high-ownership product engineering role for someone who wants to work close to the underlying financial data and build systems where correctness matters. Deep credit expertise isn’t required, but you should have experience building financial systems and be excited to develop deep expertise in credit. Your work will help make Stuut’s credit decisions explainable, auditable, and reliable as we expand the platform.

What You’ll Do

• Build and own core systems powering Stuut’s credit and financing products
• Develop reliable exposure, balance, eligibility, and limit calculations across complex financial data
• Design deterministic policy and decision systems that make credit outcomes explainable and auditable
• Model financial state across invoices, payments, credits, disputes, orders, and related events
• Build systems that safely handle delayed, duplicated, missing, or conflicting upstream data
• Create controls for reconciliation, idempotency, stale state, overrides, corrections, and failure recovery
• Integrate external credit data and internal behavioral signals into decision workflows
• Partner closely with product, data, and operations to translate real customer workflows into scalable product behavior
• Build reusable credit-domain primitives without introducing customer- or ERP-specific logic into the core system
• You Might Be a Fit If You…
• Have experience building credit, lending, payments, accounting, or other financial systems where correctness and controls matter
• Have built deterministic policy engines, decision systems, ledgers, balance calculations, or exposure systems
• Understand concepts like reconciliation, idempotency, audit trails, data provenance, and failure recovery
• Are comfortable reasoning through incomplete, delayed, duplicated, or contradictory financial data
• Think explicitly about state transitions, overrides, corrections, exceptions, and the difference between confirmed and pending financial state
• Have strong systems design and product engineering judgment and can trace a financial result back to exactly how it was produced
• Want ownership of a difficult product area and naturally question a number until you understand where it came from
• Enjoy building explicit, deterministic systems that can eventually support many different financial products
• Are highly proficient in Python and have experience working with technologies like
• Postgres, Snowflake, and AWS
• ; experience with DBOS is a plus
• Thrive in a high-growth startup where engineers work closely with the product and own problems end to end
• US Compensation
• Top-of-market salary and equity package