Anthropic
Posted Jul 10, 2026
Staff+ Software Engineer, Payment Fraud
SoHo/Hudson Square · Onsite · Senior · $320K–$485K
Help moving to NYC
Anthropic filed 61 NYC H-1Bs, Oct 2025–Jun 2026; this is a technical role. This is historical evidence, not a promise of sponsorship.
Relocation assistance is not stated in this posting.
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About the role
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 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.
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.