Atlas AI

Head of Credit & Underwriting

New York · Exec

Sponsorship not specified$50k-$500kDetected 36 days ago

PythonSQLRESTUnderwriting

About the role

Atlas is a charge card, not a revolving card.
Members pay in full every month, so the risk profile is fundamentally different and the strategy has to reflect that.
Our members have complex income, concentrated assets, and thin traditional files.

You will own every decision about who gets an Atlas card, how much they can spend, and how we manage credit risk across a portfolio of the wealthiest consumers and businesses in America.
You won't write documents and hand them off.
You'll be in the data, in the underwriting logic, and sitting with engineering to build the systems that make credit decisions in real time.
You'll own line sizing for members who spend $50K to $500K a month and need spending power that flexes with their behavior, not a static number.
You'll own the application flow so qualified members get approved fast and the rest get declined cleanly.
And you'll own the facility relationships that fund the whole portfolio.
If your instinct is to run standard FICO-based decisioning on a population of founders, family office principals, and PE partners, this isn't the right fit.
Own line sizing end to end. Build dynamic limits that expand with payment behavior and cash flow, not static tiers. A member who pays $200K on time every month should have more room than their starting line suggests. Automate it.
Own the application and onboarding pipeline.
Build the Atlas Business underwriting engine. Entity-based decisioning from Secretary of State records, business credit bureaus, bank data, and industry risk. No personal credit pulls, no personal guarantees.

8+ years in credit risk, ideally starting at a major issuer (Amex, Chase, Capital One, Citi, Discover) and then moving into an operating role at a high-growth fintech where you had to build, not just manage.
You write SQL and you're comfortable in Python or R. You've built models, not just reviewed them. You can pull data, run the analysis, and ship a recommendation the same day without waiting on an analyst.
You've worked with credit warehouse facilities: advance rates, eligibility, covenants, lender reporting. Helping negotiate or restructure one is a strong plus.
You've underwritten high-net-worth or affluent segments. You know a member with $20M in assets and a 720 FICO is not the same risk as a consumer with that score and $80K in income.
You've built infrastructure at a startup, not just optimized an existing one. You're comfortable with ambiguity, speed, and deciding with 70% of the information you'd ideally want.
You want to be in the details. You're not looking to manage a team of 20 and review their work. You want to own the outcome, build the systems, and hire a small team around you as the portfolio grows.

You write SQL and you're comfortable in Python or R.
You've built models, not just reviewed them.
You can pull data, run the analysis, and ship a recommendation the same day without waiting on an analyst.
You understand charge card economics specifically, not just revolving credit, and how that changes everything from line sizing to collections timing.
You've underwritten high-net-worth or affluent segments.
You know a member with $20M in assets and a 720 FICO is not the same risk as a consumer with that score and $80K in income.
You've built infrastructure at a startup, not just optimized an existing one.
You're comfortable with ambiguity, speed, and deciding with 70% of the information you'd ideally want.

This listing is sourced directly from Atlas AI's careers page and normalized into a canonical job model.