Software Fraud Engineer

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.

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.

Risk Engine

• 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.

Data & Analytics

• 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.

Engineering

• 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).