Position Overview

We're looking for a senior backend engineer to join a fast growing B2B credit and underwriting platform. The company turns messy business data into risk signals, applies policy, and makes fast, accurate, explainable, and auditable credit decisions. You'll own the backend and data systems that sit between engineering and data science, turning ambiguous risk and underwriting problems into reliable production systems: decisioning services, models, data contracts, credit review tools, policy execution, monitoring, audit trails, and human-in-the-loop workflows.

This is a high ownership role on a small team with real production impact. You'll partner directly with engineering, risk, and data science leadership.

Responsibilities

• Build and own production systems for underwriting, bank data review, policy execution, credit review workflows, portfolio monitoring, and risk operations.
• Translate risk models, underwriting policies, and data science requirements into reliable backend services with clear interfaces, tests, observability, rollback paths, and ownership.
• Create reusable infrastructure for evidence gathering, decisioning, monitoring, and human-in-the-loop review.
• Partner closely with risk and data science to define clean contracts between research and prototype code and production backend systems.
• Build internal tools that help the credit risk team review data, understand decisions, handle exceptions, and move faster without sacrificing correctness.
• Communicate technical assumptions, tradeoffs, failure modes, system boundaries, and migration plans clearly.
• Own ambiguous projects end to end: define the problem, propose a path, align across teams, ship production slices, measure, and iterate.
• Improve the reliability, latency, and correctness of systems that directly affect credit decisions and customer experience.

Qualifications

• 5+ years of backend engineering experience, ideally in a fast moving environment.
• Strong production backend experience with Node.js, TypeScript, and Python.
• Strong SQL skills and comfort with relational databases, data warehouses, ETL and data pipelines, and messy real world data.
• Experience designing APIs, services, jobs, data models, and contracts that other teams depend on.
• A track record of shipping systems where correctness, reliability, and operational clarity matter.
• Experience working closely with data science, credit risk, analytics, or ML teams to productionize workflows, models, policies, or decision systems.
• High agency and comfortable creating clarity when a problem is vague.
• Strong written and verbal communication across engineering and data science.
• Experience with AWS, Postgres, Snowflake, queues, async jobs, observability tooling, and third party financial APIs.
• Genuine interest in building AI native infrastructure and agentic workflows.

Nice to have: experience in payments infrastructure or credit and cashflow decision systems, policy or rules or scoring or pricing engines, productionizing ML models, LLM or agent workflows for analyst automation, and startup experience in a high ownership environment.

Location: San Francisco preferred. Exceptional remote candidates in a compatible time zone will be considered.