Software Fraud Engineer

Responsibilities Fraud Detection

We're looking for a Software Fraud Engineer to design and build our next-generation fraud prevention platform. You'll develop real-time fraud detection systems, risk engines, and automated decision-making services that protect both our users and business. This is an engineering role focused on building fraud prevention systems — not a manual fraud operations position.

• 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, Click House, 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)