Staff+ Software Engineer, Financial Fraud

Anthropic$320K — $485K *
Finance & Insurance
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Proficiency in Python, SQL, and data analysis tools
  • Experience building or operating fraud, risk, or abuse detection systems in production
  • Strong communication skills for explaining complex technical concepts to non-technical stakeholders
  • 8+ years of industry experience, particularly in payments fraud or risk (preferred)
  • Fluency with payment rails and chargeback workflows (preferred)
  • Direct experience addressing various fraud typologies (preferred)
  • Understanding of fraud loss accounting and chargeback implications (preferred)

Responsibilities

  • Design and build systems for real-time transaction risk scoring
  • Create tooling and automation for managing disputes and chargebacks
  • Engineer scalable fraud detection signals and monetization abuse detection
  • Manage a portfolio of fraud-related metrics holistically
  • Lead investigations into new fraud patterns with adaptive defenses
  • Collaborate cross-functionally with internal teams and external partners

Benefits

  • Visa sponsorship available
  • Encouragement to apply regardless of meeting all qualifications
  • Emphasis on representation and diversity in the team
  • Hybrid working policy requiring time in the office
Full Job Description
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.

Annual Salary:

$320,000-$485,000 USD

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 [redacted].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.

About Anthropic

Anthropic is an artificial intelligence research lab that focuses on developing AI systems that are safe, reliable, and trustworthy. The company was founded in 2019 by Dr. Yoshua Bengio, a leading AI researcher and winner of the Turing Award. Anthropic's research is focused on developing AI systems that can learn from small amounts of data, reason about complex systems, and interact with humans in a natural way. The company is based in New York City and has a team of experienced AI researchers and engineers.
Learn more about Anthropic
Size
50 employees
Industry
Founded
2019

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