Member of Technical Staff - Full Stack, Credit

Stuut; San Francisco (CA); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

Medical, dental & vision insurance

401(k) & Match

Equity

Flexible PTO

Parental Leave

Job summary

Stuut in San Francisco is hiring a Member of Technical Staff – Full Stack, Credit to help build the 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 own core systems with correctness and auditability as we scale the platform.

Qualifications

• Experience building credit, lending, payments, or financial systems where correctness matters.
• Experience with deterministic policy engines or decision systems.
• Knowledge of reconciliation, idempotency, audit trails, data provenance and failure recovery.
• Ability to reason through incomplete, delayed, duplicated, or contradictory financial data.
• Strong systems design and product engineering judgment; trace financial results to production.
• Proficiency in Python with experience in Postgres, Snowflake and AWS; DBOS is a plus.

Responsibilities

• 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 to 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 with product, data, and operations to translate customer workflows into scalable product behavior.
• Build reusable credit-domain primitives without ERP-specific logic.

Skills

Credit systems

Deterministic policy engines

Data reconciliation

Python

Postgres

Snowflake

AWS

System design

DBOS

Tools

DBOS

Job description

Stuut is transforming accounts receivable for B2B companies—making collections smarter and faster for companies that have historically relied on manual processes that are labor intensive and costly. Our platform is gaining traction with finance teams across industrials, chemicals, and manufacturing sectors from Fortune 10 brands to scaling midmarkets. We’re backed by top-tier investors including a16z, Khosla, Activant, 1984 Ventures, Page One and Microsoft.

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

Compensation

• Top-of-market salary and equity package

• Benefits (for U.S.-based full-time employees)

• Medical, dental & vision insurance coverage for you

• 401(k) & Match

• Equity

• Flexible PTO

• Parental Leave