Anti-Fraud Engineer

Crossmint is looking for an Anti Fraud Engineer to build fraud decisioning systems, detection controls, analyst tools, and loss measurement across financial-product flows.

You will build and own fraud decisioning services for onboarding, transfers, on/offramps, and card transactions. You will create signals, rules, models, detection controls, and analyst tools; measure fraud outcomes; respond to incidents; review product designs; and support compliance evidence and client-facing fraud investigations.

• Build and own services that score and decide onboarding attempts, stablecoin transfers, on/offramp orders, and card transactions.
• Turn analyst judgment into production rules and models with thresholds, versioning, backtesting, and rollback paths.
• Build device, behavior, velocity, counterparty, and graph-relationship signals across clients and wallets.
• Measure and publish catch rate, false-positive rate, and fraud loss per product line.
• Build detection for account takeover, mule networks, first-party fraud, synthetic identities, refund and promo abuse, and agent-initiated payment abuse.
• Lead the engineering response to fraud incidents by containing losses, finding root causes, and closing product gaps.
• Participate in the on-call rotation.
• Build analyst tools including case management, queues, reason codes, and self-service rule tuning.
• Evaluate, select, and integrate fraud tooling and monitoring platforms.
• Produce system-generated evidence for compliance filings, audits, and supervisory review.
• Review new-product designs to identify fraud surfaces before launch.
• Work with client-facing teams on client fraud issues.
• Keep current on fraud tooling, onchain tracing, and AI-native engineering workflows.

• 5+ years building production systems, including 3+ years focused on fraud, risk, or trust and safety.
• Experience reducing and measuring fraud losses at a payments, card, banking, lending, marketplace, or crypto-exchange company.
• Hands-on ownership of a production rules engine or model-serving path and its supporting data pipeline.
• Strong programming skills in at least one modern language; TypeScript is preferred.
• Knowledge of catch rate, false-positive rate, precision at threshold, and loss rate.
• SQL and independent data-analysis skills.
• Ability to weigh fraud-loss prevention against customer friction.
• Deep familiarity with current AI and agentic tools and their impact on fraud.
• Bachelor's degree in Computer Science or equivalent professional experience.
• Experience with stablecoins, wallet infrastructure, blockchain payment rails, onchain tracing, or address risk is preferred.
• Experience with card-scheme fraud, chargebacks, disputes, monitoring programs, 3DS, or SCA exemptions is preferred.
• Experience with KYC/KYB onboarding abuse or synthetic identity detection is preferred.
• Experience with commercial fraud and monitoring platforms is preferred.
• Experience with BSA/OFAC, PSD2/SCA, MiCA, DORA, or SOC 2 is preferred.

• Stock options for full-time employees.
• Access to leading AI tools and subscriptions.
• Unlimited flexible PTO.
• Parental leave program.
• Flexible work schedule.
• Company laptop and allowance for necessary home equipment.
• Daily stipend for commuting to the office and/or meals.
• Two company-paid off-sites each year.
• Health and dental insurance.

Initial video call with a team member.