We are seeking a seasoned Solution Architect to lead the design, development, and optimisation of enterprise-grade solutions integrating with fraud detection and prevention systems.
The ideal candidate will have extensive experience in fraud risk engine product integration, fraud detection techniques, and a strong understanding of financial crime prevention strategies, including integration with cloud-based data stores such as AWS.Key Responsibilities:Design and architect scalable, effective real-time fraud risk management solutions utilising advanced fraud detection engines.Lead the integration of fraud risk engines with existing transaction processing systems and cloud-based data stores such as AWS S3, Aurora, Redshift, DynamoDB, and stream processing tools like AWS Kinesis and Kafka.Implement data pipelines and workflows to support real-time fraud detection and reporting using AWS services.Architect end-to-end orchestration frameworks to manage data ingestion, transformation, enrichment, alerting, and workflow management in real time.Continuously monitor, evaluate, and improve the effectiveness of fraud detection systems.Collaborate with cross-functional teams including engineering, data science, compliance, and business units to implement new fraud prevention initiatives.Stay updated on emerging fraud trends, techniques, and regulatory changes impacting fraud risk management.Provide expertise during audits and compliance reviews related to fraud prevention controls.Ensure that products are developed in accordance with the overall architectural strategy and that the development team adheres to valid design guidelines and standards.Own the technical solution throughout the implementation lifecycle.Act as a trusted advisor to clients, helping them make informed decisions and optimise the use of risk engines across the fraud ecosystem.Required Skills & Experience:Bachelor's or Master's degree in Computer Science, Information Security, Data Science, or a related field.8+ year of overall experience in architecture and enterprise system design with 5+ years in designing and implementing fraud risk engines and detection systems.Deep understanding of fraud schemes, payment processing, and financial crime prevention.Extensive knowledge of fraud detection technologies, including rules-based, machine learning, and AI-driven solutions.Strong programming skills in languages such as Java, Python, or similar.Experience with fraud prevention platforms and tools (e.g., FICO, SAS, Quantexa, Actimize, or similar).
Hands-on experience with cloud services, especially AWS data stores (e.g., S3, Redshift, DynamoDB, RDS), including data ingestion, storage, and retrieval for fraud detection pipelines.Knowledge of data analysis, feature engineering, and big data technologies.Familiarity with regulatory requirements regarding fraud prevention (e.g., PCI DSS, AML).
Risk engine product certification.Preferred Qualifications:Experience in solutioning and leading multiple end-to-end risk engine product integration projects (POCs, pilots, or implementations).
Experience with cloud-based fraud detection solutions and AWS cloud architecture.Understanding of APIs and microservices architecture for fraud systems.Strong analytical and problem-solving skills.