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Software Fraud Engineer

You will design and build fraud prevention systems for payments, wallets, authentication, and user activity. You will develop real-time fraud pipelines, risk engines, decision services, APIs, and backend tooling; analyze behavioral and transactional data; investigate emerging fraud patterns; optimize detection accuracy and latency; and deploy countermeasures with cross-functional teams.

Responsibilities

  • Design and develop fraud detection systems for payments, wallets, authentication, and user activity
  • Detect account takeover, payment fraud, bonus abuse, multi-accounting, and other abuse scenarios
  • Build real-time fraud pipelines and event processing systems
  • Develop automated fraud prevention mechanisms
  • Build and improve fraud rules, velocity controls, and dynamic risk scoring
  • Design decision engines for transaction approval, review, or rejection
  • Optimize fraud detection accuracy while minimizing false positives
  • Improve fraud models using behavioral and transactional data
  • Analyze transaction patterns, user behavior, device intelligence, and risk signals
  • Work with large-scale event streams and transactional datasets
  • Create internal investigation and monitoring tools for Fraud, Support, and Compliance teams
  • Investigate emerging fraud patterns and rapidly deploy countermeasures
  • Develop scalable backend services supporting fraud prevention
  • Build APIs and internal tooling for risk evaluation
  • Optimize latency for real-time fraud decisions
  • Collaborate with Product, Payments, Data, and Platform teams

Requirements

  • 4+ years of software engineering experience
  • Experience building fraud prevention, risk, payment, banking, fintech, or security systems
  • Strong backend development experience with Go, Java, Kotlin, Python, or similar
  • Experience working with distributed systems and event-driven architectures
  • Strong SQL skills and experience with large datasets
  • Understanding of payment flows, authentication, and transactional systems
  • Experience designing real-time decision engines
  • Strong analytical and problem-solving skills
  • Fluent English
  • Experience in crypto, Web3, or blockchain
  • Experience with Kafka, ClickHouse, Redis, Elasticsearch, or similar technologies
  • Experience with machine learning models for fraud detection
  • Knowledge of AML, KYC, or payment risk systems
  • Experience with device fingerprinting, behavioral analytics, or identity verification

Benefits

  • Support for courses, conferences, and English learning with up to 100% coverage
  • Remote or hybrid work with flexible hours
  • Up to 20 vacation days, 8 company holidays, and 5 personal days per year
  • Structured performance reviews and team awards
  • Retreats in international locations

See also

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