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Manage the software engineering team for the Fraud Management Platform, providing technical leadership and driving system architecture for fraud prevention solutions.

Lead domain product vision and roadmap for Mastercard's real-time, event-driven payment platforms. Define epics, features, and measurable outcomes; collaborate with engineering and cross-functional teams to deliver, operate, and improve scalable, resilient messaging platforms (Axon/Kafka, NATS). Drive agile practices, CI/CD, TDD/BDD, post-launch reviews, and operational stability while engaging global stakeholders and managing delivery across distributed teams.

Develop and test high-performance, low-latency Java-based fraud detection capabilities on Mastercards Decision Management Platform. Collaborate in an Agile team to design, implement, unit-test, troubleshoot, and document scalable services, working with product and technical stakeholders to meet delivery timelines.

Design, build, and maintain scalable data pipelines and ML systems at petabyte scale using Databricks/Spark. Partner with data science to productionize models, implement testing/monitoring, ensure compliance, and optimize ETL/ELT for merchant identity and fraud-risk applications.

Develop and productionize ML/AI models and scalable data science capabilities for merchant risk assessment. Work on data extraction, feature engineering, entity resolution, prototyping models, validating and monitoring performance, and building Databricks/Spark-based workflows in collaboration with Data Science, Product, and Engineering teams.

Support security operations through incident, vulnerability, and threat management; maintain security posture (IAM, key management, scans, hardening); automate tasks in the SIEM; respond to incidents; document risks and controls; participate in audits and on-call rotation; evaluate and improve security tools and processes.

This role involves developing high performance, low latency Java solutions for the Fraud Management Platform, collaborating with a team in an Agile environment, and troubleshooting operational issues.

Lead end-to-end delivery of technical programs for Customer Platform Experience. Coordinate product, engineering, and architecture teams in an Agile/Scrum environment, manage roadmaps, dependencies, risks, and stakeholder communications, and drive predictable, high-quality outcomes while improving processes and operating models.

Lead design, development, deployment, and monitoring of production ML models for merchant risk, fraud, AML, and payment-related use cases. Own feature engineering, model lifecycle, validation, production support, and cross-functional collaboration to deliver high-quality, interpretable, and scalable ML solutions using large-scale transaction and merchant data.

The Senior Software Engineer will enhance IBM ODM Rule solutions, focusing on fraud rule engines, large-scale migrations, and platform modernization while ensuring high availability and low latency solutions.