Senior Backend Engineer, Risk Systems

Slope • San Francisco, CA

5d • Hybrid

About The Position

Slope builds financial infrastructure for B2B commerce, helping growing businesses access capital and enterprise credit teams make faster, better, more automated decisions. At the core of Slope is underwriting: understanding messy business data, turning it into risk signals, applying policy, and making decisions that are fast, correct, explainable, and auditable. We are looking for a senior backend engineer to own the systems that make that possible. This role involves building the backend and data systems that sit between Engineering, Risk, Data Science, Product, and Operations. It is not a pure ML research role or a narrow payments-infra role. The primary focus is on turning ambiguous risk and underwriting workflows into reliable production systems, including decisioning services, data contracts, analyst tools, policy execution, monitoring, audit trails, and human-in-the-loop workflows. The ideal candidate is excited by complex problems where the initial task is problem definition rather than immediate coding.

Requirements

• 5+ years of backend engineering experience, preferably in a fast-moving environment.
• Strong production backend experience with Node.js and Python.
• Strong SQL skills and comfort working with relational databases, data warehouses, ETL/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, auditability, 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 proactive: you do not need fully specified tickets, and you know how to create clarity when the problem is vague.
• Strong written communication. You can explain tradeoffs, failure modes, and system boundaries in a way that earns trust across Engineering, Risk, Product, and Ops.
• Product judgment for internal users. You care whether the system actually improves underwriting decisions and workflows, not just whether the code shipped.

Nice To Haves

• Experience in payments infrastructure, or credit / cashflow decision systems.
• Experience building policy engines, rules systems, scoring systems, pricing systems, analyst review tools, or operational decisioning platforms.
• Experience productionizing ML models, monitoring model behavior, building eval workflows, or supporting human-in-the-loop review.
• Experience with LLM or agent workflows for analyst automation, QA, monitoring, or evidence gathering.
• Experience with AWS, Postgres, Snowflake, queues, async jobs, observability tooling, and third-party financial APIs.
• Startup experience, especially in a high-ownership environment.

Responsibilities

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

Benefits

• Unusually high ownership: small team, important surface area, real production impact.
• Partner directly with Engineering, Risk, Data Science, Product, and Operations.
• Help build the operating system for B2B credit: faster decisions, better workflows, stronger auditability, and more scalable underwriting.
• Backed by top investors including Y Combinator, Union Square Ventures, and leading founders/operators across fintech and technology.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed