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.

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.

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.

Requirements

- 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.

Nice to have
- 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
- 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).