Software Fraud Engineer
Indexed description
This is an engineering role focused on building fraud prevention systems — not a manual fraud operations position.
Responsibilities
Fraud Detection
- 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
- Continuously 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 closely with Product, Payments, Data, and Platform teams
- 4+ years of software engineering experience
- Experience building fraud prevention, risk, payment, banking, fintech, or security systems
- Strong backend development experience (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
- Professional growth: support for courses, conferences, and English learning (up to 100% coverage)
- Work-life fit: remote or hybrid format with flexible hours across international teams
- Paid leave: up to 20 vacation days + 8 company holidays + 5 personal days per year
- Recognition programs: structured performance reviews and team awards
- Team culture: retreats in international locations (for example, company apartments in Cyprus)
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