Staff+ Software Engineer, Financial Fraud

Doist; New York, Seattle, San Francisco (NY, WA, CA); Hybrid; USD 320,000 - 485,000; Full time

Job summary

Anthropic is seeking a Software Engineer for Fraud Prevention to build real-time risk decisioning, manage dispute and chargeback lifecycles, and detect monetization abuse across subscriptions and promotions.

You will design scalable fraud signals and work with finance, legal, data science, and payment processors to own a portfolio of metrics like loss rate and authorization impact.

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 trade-offs to non-technical stakeholders.

Responsibilities

• Design and build real-time risk decisioning that scores transactions at authorization time.
• Build tooling for dispute and chargeback lifecycle from review queues to evidence collection.
• Engineer fraud signals at scale—device fingerprinting, BIN and issuer signals, velocity features, and cross-account linkage.

Skills

Python

SQL

Data analysis

Fraud/risk systems

Communication

Education

Bachelor's degree

Job description

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for users and society. The team is a quickly growing group of researchers, engineers, policy experts, and business leaders building beneficial AI systems.

About the role

The Fraud Prevention team protects Anthropic's payment and monetization surfaces from financial abuse. As a software engineer on this team you will build 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.

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 a 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, data science, and 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 trade‑offs to non‑technical stakeholders.

Preferred Qualifications

• 8+ years of industry software engineering experience, focused 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, iVFMP, 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.

Compensation

Annual Salary: $320,000 — $485,000 USD.

Employment Details

Minimum education: Bachelor’s degree or equivalent combination of education, training, and experience. Minimum years of experience: As required for the internal job level.

Location: Hybrid policy—staff are expected to be in an office at least 25% of the time. Some roles may require more time onsite.

Visa sponsorship: We sponsor visas and will make reasonable efforts to obtain a visa for an offer recipient.