Staff+ Software Engineer, Financial Fraud

Job summary

ABOUT Ant*** Ant***’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

Benefits

Qualifications

• Proficiency in Python, SQL, and data analysis
• 8+ years of industry software engineering experience, with a focus on payments fraud or risk
• Fluency with payments rails: card networks, payment service providers (e.g., Stripe, Adyen), in-app purchase platforms (Apple, Google), refund flows, and the chargeback and dispute lifecycle
• Direct experience combating fraud typologies such as card testing, stolen-card monetization, refund and chargeback abuse, subscription and trial abuse, promotional abuse, and friendly fraud
• Understanding of fraud loss accounting — fraud loss vs.
• dispute fees vs.
• card network monitoring programs (e.g., VDMP, i VFMP, Mastercard ECP) — and why chargeback rate thresholds carry existential stakes
• Experience building hybrid rules-and-ML risk systems: real-time scoring at authorization plus post-authorization review workflows
• Experience at a marketplace or subscription business, or on a processor-side or issuer-side risk team
• The annual compensation range for this role is listed below.
• For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
• Annual Salary:

Responsibilities

• Payments fraud is more externally coupled than most trust and safety work — you'll collaborate closely with finance, support, and legal teams internally, and with payment processors and platform partners externally.
• Design and build real-time risk decisioning that scores transactions at authorization time, balancing fraud loss, approval rates, and latency constraints
• Build tooling and automation for the dispute and chargeback lifecycle, from review queues to evidence collection and loss reporting
• Own a portfolio of metrics — loss rate, dispute rate, authorization approval impact, and false-positive rate — rather than optimizing any single number
• Lead investigations into emerging fraud patterns, building multi-layered defenses designed for attacker adaptation rather than point-in-time rules
• Work cross-functionally with finance, support, legal, and data science, and with external payment processors and platform partners
• MINIMUM

Skills

Degrees

Industry