Staff+ Software Engineer (Payment Fraud)
Posted Updated
- 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
- 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
Benefits
- Comprehensive health, dental, and vision insurance for you and your dependents
- Inclusive fertility benefits via Carrot Fertility
- 22 weeks of paid parental leave
- Flexible paid time off and absence policies
- Mental health support for you and your dependents
- Competitive salary and equity packages
- Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
- Retirement plans with competitive matching
- Life and income protection plans
- $500/month flexible wellness and time saver stipend
- Commuter benefits
- Annual education stipend
- Home office stipends
- Relocation support for those moving for Anthropic
- Daily meals and snacks in the office
- Proficiency in Python, SQL, and data analysis tools
- Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
- Experience building or operating fraud, risk, or abuse detection systems in production
- Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
- Strong communication skills and ability to explain complex technical tradeoffs to non-technical stakeholders
- Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
- We encourage you to apply even if you do not believe you meet every single qualification
- Experience building hybrid rules-and-ML risk systems: real-time scoring at authorization plus post-authorization review workflows
- 8+ years of industry software engineering experience, with a focus on payments fraud or risk
- Experience at a marketplace or subscription business, or on a processor-side or issuer-side risk team
- 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
