Automation Tester- AI (Banking Domain)

Role: Automation Tester — AI (Banking Domain)

This role is with our client who is leading financial institution modernizing our digital platforms. Our client combine rigorous risk and compliance standards with data-driven product innovation. We’re hiring an Automation Tester with AI experience to strengthen QA capability for critical banking applications and to help embed intelligent testing, test automation,and ML-driven validation into our delivery lifecycle.

Role overview

As an Automation Tester — AI, you will design, build and maintain automated test solutions for banking applications, and apply AI/ML techniques to improve test coverage, defect detection, and test efficiency. You will work closely with engineering, product, security, and operations teams to ensure high-quality releases that meet functional, regulatory, and performance requirements for retail and corporate banking products.

Key responsibilities

• Design, develop and maintain automated test suites for functional, integration, regression, API, UI, and performance testing across web, mobile, and backend banking systems.
• Integrate AI/ML techniques to enhance testing — e.g., intelligent test-case prioritization, flaky-test detection, anomaly detection in logs/metrics, visual UI validation, test-data generation, and predictive defect analytics.
• Create and maintain test frameworks, reusable libraries, and test automation pipelines integrated into CI/CD (e.g., GitLab/GitHub Actions/Jenkins).
• Collaborate with business analysts, product owners, developers and architects to define test strategies that cover regulatory, security, anti-fraud, and data privacy requirements.
• Develop robust test data management approaches for sensitive banking data, including anonymization, synthetic data generation, and secure test environments (including air-gapped or restricted setups).
• Implement and maintain API-first testing (REST/gRPC) and contract testing where applicable.
• Execute performance and scalability testing for critical payment, transaction, and settlement flows; analyze results and recommend remediation.
• Build dashboards and reports for test health, coverage, defect trends, and AI-driven quality insights.
• Participate in root-cause analysis for defects, coach teams on quality practices, and promote shift-left testing in Agile/Scrum/SAFe environments.
• Ensure test artifacts meet auditability and compliance standards required in the banking domain.

Required qualifications

• 3–7+ years of software testing/quality assurance experience with strong hands-on automation experience.
• Proven experience with automation tools and frameworks (e.g., Selenium, Playwright, Cypress, Appium) and test frameworks in Java, Python, or JavaScript/TypeScript.
• Practical experience applying AI/ML methods to testing problems — e.g., model-based testing, anomaly detection, NLP for test-case generation/maintenance, or supervised learning for defect prediction.
• Hands-on with API testing and tools such as Postman, RestAssured, Pact, or similar.
• Experience integrating automated tests into CI/CD pipelines and using test orchestration tools.
• Familiarity with performance testing tools (JMeter, Gatling, k6) and interpreting performance metrics.
• Strong knowledge of banking domain concepts: payments, accounts, loans, KYC/AML, transaction flows, and relevant regulations (e.g., PSD2, PCI-DSS, GDPR as applicable).
• Understanding of secure software development and testing practices, including data protection and secure test environments.
• Experience working with databases and writing SQL for verification and test data setup.
• Excellent analytical, communication, and collaboration skills.
• Bachelor’s degree in Computer Science, Engineering or equivalent experience.

Preferred qualifications

• Hands-on experience with MLOps/ModelOps tools or platforms and familiarity with ML lifecycle (training, validation, inference monitoring).
• Knowledge of observability and log analytics tools (ELK/Elastic Stack, Splunk, Prometheus/Grafana) to enable AI-driven test insights.
• Experience with cloud platforms and IaC (Azure, AWS, Terraform, ARM/Bicep) for test environment provisioning.
• Experience in regulated banking environments or with enterprise-scale critical systems.
• Certifications in testing (e.g., ISTQB) or cloud/AI certifications are advantages.
• Experience building or contributing to synthetic data generators, test-data factories, or privacy-preserving data techniques.

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