Back End Engineer - Fintech infra

Back End Engineer — Underwriting

Palo Alto, CA or New York, NY · Hybrid · Full-time (Relocation supported)

$140K–$250K base + 0.05%–0.17% equity

The company

This company is building mortgage infrastructure that lets lenders scale through software, not people. The platform automates credit, compliance, capital, and the internal tooling that usually lives in spreadsheets, inboxes, and manual review queues.

Leading fintechs, lenders, and publicly traded banks already use the platform to originate loans.

The team is about 40 people, the company was founded in 2022, has raised $45M, and is backed by Conversion Capital, Peter Thiel, QED Investors, and Citi.

The role

This is a backend role for engineers who want ownership of the systems that decide whether a loan can move forward. The work sits at the intersection of underwriting policy, internal tooling, and AI-assisted decision support.

You will encode dense mortgage guidelines into executable logic using TypeScript, custom DSLs, and AI, then turn that logic into software that is precise enough for production underwriting and flexible enough for ongoing rule changes.

You will work directly with mortgage experts to capture nuance, exceptions, and edge cases, and convert that domain knowledge into systems that can be tested, audited, and trusted.

The technical problem

Mortgage underwriting is exception-heavy. Eligibility can depend on borrower profile, income source, property type, documentation quality, and program-specific rules that are simple to describe in prose and easy to misencode.

The hard part is not building isolated automation. The hard part is building a system where policy, configuration, AI assistance, and human review work together without brittle one-off logic or silent failure modes.

Precision matters because a wrong decision can delay a closing, change loan economics, or create expensive downstream risk.

What you'll own

• Underwriting logic: translate mortgage guidelines and exceptions into executable code.
• Decisioning abstractions: help shape the DSLs and internal interfaces underwriters use to configure and guide automated decisions.
• AI-assisted workflows: use AI where it adds leverage, while preserving determinism, reviewability, and audit trails.
• Testing and validation: build regression coverage around edge cases, policy changes, and failure modes.
• Domain translation: work with mortgage experts to extract nuance that is not obvious from written guidelines.
• Reliability: keep critical underwriting systems predictable as volume and rule complexity grow.

Who this is for

You are likely a fit if you have:

• 3+ years as a software engineer, with enough depth to own systems end to end.
• Experience building backend or decisioning systems in regulated or high-stakes domains such as fintech, lending, payments, insurance, or healthcare.
• Strong judgment around business rules, edge cases, and technical correctness.
• Experience with test design, validation, or production debugging where failures were expensive.
• Comfort working closely with non-technical domain experts.
• Interest in AI/ML tooling, DSLs, workflow orchestration, or rule engines.
• Experience with systems where policy was code, or with compilers and interpreters, is a strong signal.
• The ability to explain why a design should be explicit, configurable, or abstracted.

Tech stack

• Backend: TypeScript
• Core surface area: custom DSLs, underwriting logic, AI-assisted decision support

The exact abstractions are still evolving. The important part is being able to shape them well.

Why now

The platform already has real customers and real underwriting complexity.

The next constraint is not proof of concept. It is building the underwriting layer to support more volume, more policy variation, and more automation without losing correctness.

The architectural decisions made here will determine how much of the mortgage lifecycle can be automated safely over the next few years.

This role is not for you if

• You need fully specified tickets before you can start.
• You want isolated feature work with little domain complexity.
• You are uncomfortable making architecture decisions in ambiguous, regulated environments.
• You prefer velocity that comes from looser correctness standards.
• You do not want to work directly with subject matter experts.

Compensation and logistics

• Base salary: $140K–$250K
• Equity: 0.05%–0.17%
• Location: Palo Alto, CA or New York, NY
• Work model: hybrid, with a strong preference for Palo Alto
• Office expectation: at least 3 days per week
• Remote: possible only for a truly exceptional candidate
• Visa sponsorship: available, including new H1B applications
• Employment: full-time

About Aurora

Aurora helps exceptional engineers find the right role at some of the most ambitious startups worldwide.

We work with teams that value high ownership, strong technical standards, and clear scope.