Job Overview
Engineer — Real-Time Fraud Detection Systems
Location: Riyadh, Saudi Arabia
Seniority Level: Senior / Principal Engineering Track
Employment Type: Full-time, Permanent
Industry: Fintech, Fraud Technology, Payments, Cybersecurity, Financial Analytics
Work Model: Remote-first
Engineering Mission
We are seeking a technically strong Real-Time Fraud Detection Systems Engineer to develop infrastructure capable of identifying suspicious financial activity as transactions occur.
The role combines software engineering, event streaming, machine-learning integration, transaction processing, and financial-risk technology.
Engineering Responsibilities
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Design and develop real-time transaction-monitoring services.
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Build low-latency systems capable of processing high-volume financial events.
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Integrate fraud-detection models into production transaction environments.
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Develop event-driven architectures for real-time risk scoring.
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Build APIs and services connecting transaction systems with fraud engines.
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Implement automated rules, scoring mechanisms, and anomaly-detection workflows.
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Optimise system latency, throughput, reliability, and fault tolerance.
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Develop monitoring and observability for fraud-detection infrastructure.
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Work with data scientists to productionise predictive models.
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Collaborate with cybersecurity and risk teams on emerging fraud patterns.
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Conduct technical investigations following detection failures or production incidents.
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Develop automated testing for critical fraud-detection components.
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Contribute to architecture reviews and platform-modernisation initiatives.
Technical Requirements
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Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field.
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5–9 years of software engineering experience.
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Strong proficiency in Java, Python, Go, C++, or comparable languages.
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Experience with event-streaming platforms such as Kafka or equivalent.
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Strong knowledge of APIs, microservices, databases, and distributed systems.
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Experience with machine-learning integration is highly desirable.
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Understanding of payment systems and transaction processing.
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Familiarity with cloud platforms, containers, CI/CD, and observability tooling.
Technical Environment
Real-Time Analytics | Fraud Detection | Event Streaming | Machine Learning | Microservices | Payment Systems | Low-Latency Engineering | Cloud Infrastructure
Indicative Compensation
SAR 38,000–58,000 monthly + benefits, depending on engineering depth and experience.
Engineering Outcome
Develop a fraud-detection platform capable of analysing transactions in near real time, identifying anomalous behaviour rapidly, and supporting high-volume financial operations without compromising performance or reliability.
Are you excited about this opportunity?
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