Staff+ Software Engineer, Financial Fraud

The shape of it

In the posting’s own words

The Fraud Prevention team protects Anthropic's payment and monetization surfaces from financial abuse — keeping fraud losses, dispute rates, and network monitoring exposure in check while preserving a smooth experience for legitimate customers. As a software engineer on this team, you will build the systems that make risk decisions in real time, manage the dispute and chargeback lifecycle, and detect monetization abuse across subscriptions, in-app purchases, and promotions. The ideal candidate can see things from attackers' perspectives, anticipate their responses to countermeasures, and never loses sight of the fact that a false positive here is a paying customer.

What it asks for · 3

• Proficiency in Python, SQL, and data analysis tools
• Experience building or operating fraud, risk, or abuse detection systems in production
• Strong communication skills and ability to explain complex technical tradeoffs to non-technical stakeholders

Also a plus

• 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

What the job covers

• 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
• Engineer fraud signals at scale — device fingerprinting, BIN and issuer signals, velocity features, and cross-account linkage — and detect monetization abuse across subscriptions, trials, promotions, and in-app purchases
• 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

Tools and skills named

Words the posting leans on

• fraud12×
• abuse7×
• payment7×
• dispute6×
• experience6×
• rate6×
• risk6×
• chargeback5×
• monetization4×
• subscription4×
• authorization3×
• build3×
• card3×
• fraud loss3×
• systems3×
• approval2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

More open at Anthropic

• Account Executive, AI NativeNew York City, NY; San Francisco, CA | New York City, NY
• Account Executive - DNBSingapore
• Account Executive, Public SectorSydney, Australia
• Account Executive - Public Sector (ASEAN)Singapore
• Accounting, Revenue Internal ControlsSan Francisco, CA | Seattle, WA
• AI Fluency Education LeadSan Francisco, CA | New York City, NY