Software Fraud Engineer

Gomining; United States; Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

Remote or hybrid work

Career development

Paid time off and holidays

Recognition programs

Team retreats

Job summary

Gomining is seeking a Software Fraud Engineer to design and build our 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.

This engineering role focuses on building fraud prevention systems—not manual fraud operations. You will collaborate with Product, Payments, Data, and Platform teams to scale backend services and APIs for risk evaluation.

Qualifications

• 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.

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.

Skills

Software engineering

Backend development

Distributed systems

SQL

Go

Java

Kotlin

Python

Real-time decision engines

Problem solving

English fluency

Kafka

ClickHouse

Redis

Elasticsearch

ML for fraud detection

Tools

Kafka

ClickHouse

Redis

Elasticsearch

ML for fraud detection

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).