# Staff+ Software Engineer, Payment Fraud  at Anthropic

- Company: Anthropic (anthropic.com)
- Location: San Francisco, CA | New York City, NY | Seattle, WA
- Places: San Francisco, New York, Seattle
- Posted: 2026-07-10
- Apply: https://job-boards.greenhouse.io/anthropic/jobs/5325909008
- Page: https://ye.saranatour.dev/jobs/staff-software-engineer-payment-fraud-anthropic-kn74r6hx4y2nbc0nvwb76svkmh8hd886

## The posting

Staff+ Software Engineer, Payment Fraud 
Anthropic · San Francisco, CA | New York City, NY | Seattle, WA

## **About Anthropic**

Anthropic’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.

## **About the role**

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.

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.

## **Responsibilities:**

- 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

## **Minimum Qualifications:**

- 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

## **Preferred Qualifications:**

- 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