Software Fraud Engineer

GoMining; Poland; On-site; PLN 180,000 - 270,000; Full time

Benefits offered by this job

Remote or hybrid format

Flexible hours across international-te

Paid leave: 20 vacation days + 8 hols

Personal days: 5 per year

Company retreats in international locs

English learning support (up to 100%)

Job summary

GoMining is seeking a Software Fraud Engineer to design and build a next-generation fraud prevention platform. You will develop real-time fraud detection systems, risk engines, and automated decision-making services to protect users and business.

The role focuses on engineering fraud prevention systems, not manual fraud operations. It requires 4+ years of backend experience, proficiency in Go/Java/Kotlin/Python, and work with distributed, event-driven architectures.

Qualifications

• 4+ years of software engineering experience.
• Experience building fraud prevention, risk, payment, banking, fintech, or security systems.
• Strong backend development experience in Go, Java, Kotlin, or Python.
• Experience with distributed systems and event-driven architectures.
• Strong SQL skills and working with large datasets.
• Fluent English.

Responsibilities

• Fraud Detection: Design and develop fraud detection systems for payments, wallets, authentication, and user activity.
• Risk Engine: Build and improve fraud rules, velocity controls, and dynamic risk scoring.
• Data & Analytics: Analyze transaction patterns, user behavior, device intelligence, and risk signals.
• Engineering: Develop scalable backend services supporting fraud prevention and build APIs for risk evaluation.
• Collaborate with Product, Payments, Data, and Platform teams and optimize latency for real-time decisions.

Skills

Go

Java

Kotlin

Python

Distributed systems

Event-driven architecture

SQL

Data analysis

English fluency

Tools

Kafka

ClickHouse

Redis

Elasticsearch

Job description

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.

• 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.

• 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).