About the Role
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.
Requirements
•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.
Responsibilities
•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.
Benefits
•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.
Hiring Process
Initial video call with a team member.
