Software Fraud Engineer

GoMining; España; On-site; USD 120,000 - 170,000; Full time

Benefits offered by this job

Remote or hybrid format

Flexible hours across international时间

Professional growth: courses and英语言培训

Paid leave and holidays

Company retreats

Job summary

GoMining is hiring 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 that protect users and the business.

The role focuses on engineering fraud prevention systems rather than operations. You will work on fraud detection, risk scoring, data analytics, and scalable backend services, collaborating with cross-functional teams across the company.

Qualifications

• 4+ years of software engineering experience.
• Experience building fraud prevention, risk, payments, banking, fintech, or security systems.
• Strong backend development experience.
• 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.
• Fluent English.

Responsibilities

• Design and build real-time fraud detection systems for payments, wallets, authentication, and user activity.
• Develop risk engines, rules, and dynamic scoring.
• Create automated decision-making services for transaction approval, review, or rejection.
• Build scalable backend services and APIs for risk evaluation.
• Collaborate with Product, Payments, Data, and Platform teams.

Skills

Backend development

Distributed systems

Go

SQL

Real-time decision engines

Fraud prevention experience

English fluency

Payments/Fintech knowledge

Tools

Kafka

ClickHouse

Redis

Elasticsearch

Go

Job description

Responsibilities

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

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)