Solution Architect – Fraud Risk Engines

Job description

Job Description

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.

Qualification

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.
   

Locations

Melbourne

Canberra

Sydney

Additional Information

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Required Skill Profession

Computer Occupations