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The Senior UAT Test Engineer will lead end-to-end User Acceptance Testing (UAT) for Fraud Detection systems within BFSI applications. This role requires deep expertise in fraud risk, AML, and transaction monitoring systems, along with strong leadership in driving UAT strategy, stakeholder collaboration, and ensuring regulatory compliance. The candidate will act as a bridge between business, QA, and development teams to ensure high-quality fraud detection solutions.
Job Responsibility
Lead UAT planning, strategy, and execution for Fraud Detection systems
Define UAT scope, test approach, timelines, and entry/exit criteria
Review and validate business requirements, fraud rules, and detection logic
Oversee design and execution of complex UAT scenarios, including high-risk fraud cases
Validate end-to-end transaction monitoring, alert generation, scoring, and case management workflows
Ensure accuracy of fraud detection outcomes and minimize false positives/negatives
Drive defect management lifecycle: triage, prioritization, root cause analysis, and closure
Collaborate closely with business stakeholders, SMEs, and product owners for sign-offs
Ensure compliance with regulatory standards (AML, KYC, PCI-DSS, etc.)
Provide insights and recommendations to improve fraud detection effectiveness and UAT processes
Lead UAT status reporting, dashboards, and stakeholder communications
Mentor and guide junior and intermediate testers
Support automation initiatives and continuous improvement in UAT practices
Requirements
6–10 years of experience in BFSI testing with significant UAT experience
Strong domain expertise in Fraud Detection, AML, Risk, or Financial Crime systems
Proven experience in validating fraud rules engines and transaction monitoring systems
Strong understanding of end-to-end payment flows and fraud risk controls
Hands-on experience with defect management tools (e.g., JIRA, ALM)
Ability to lead UAT cycles and manage multiple stakeholders
Excellent analytical skills for fraud pattern identification and validation
Strong communication, leadership, and stakeholder management skills
Experience in Agile, Scrum, or hybrid delivery models
Nice to have
ISTQB Advanced Certification or relevant QA certifications
Experience with tools like Actimize, FICO, SAS Fraud Management, or similar platforms
Strong SQL and data analysis skills
Exposure to AI/ML-based fraud detection systems
Knowledge of Claims or Risk domain
Experience in test automation or UAT optimization frameworks