Full Description

Experience- 7- 10 years Location- Hyderabad- Notice period- Immediate JD- Strong experience in software quality engineering, test strategy, test planning, and QA leadership across enterprise applications. Expertise in UI automation testing using Selenium and Playwright or equivalent frameworks. Experience designing and implementing test automation frameworks using Java, Python, JavaScript, or similar technologies. Strong experience in functional, integration, regression, system, and end-to-end testing. Strong knowledge of Agile/Scrum, Shift-Left Testing, Continuous Testing, and Quality Engineering practices. Strong understanding of JSON, XML, REST APIs, SOAP, web services, and microservices architectures. Strong experience with cloud environments, preferably Pivotal Cloud Foundry and/or AWS/Azure/GCP. Knowledge of Splunk or equivalent production monitoring tools for log analysis, troubleshooting, and root-cause identification. Experience establishing QA metrics, quality gates, defect management, test coverage, and release-readiness criteria. Ability to lead test automation strategy and framework modernization, reducing manual testing and improving release velocity. Strong experience in AI-led Quality Engineering, leveraging AI/GenAI capabilities to improve test planning, test design, automation, execution, defect analysis, and overall software quality. Preferably generating test case and script creation using copilot. Experience using AI-assisted test generation and automation tools to generate test scenarios, test cases, automation scripts, regression suites, and test data. Experience leveraging AI/GenAI for defect analysis, root-cause analysis, log analysis, failure prediction, and intelligent test prioritization. Experience evaluating and adopting AI-powered QA/testing tools to improve testing efficiency, coverage, productivity, and quality. Hands-on experience with AI development/productivity tools such as GitHub Copilot or equivalent AI tools, with the ability to apply them effectively in QA automation and Quality Engineering activities. Ability to identify opportunities where AI can replace or augment repetitive manual QA activities and drive measurable improvements in automation and productivity. Understanding of AI/ML application testing, including validation of AI-driven functionality, data quality, model behavior, accuracy, reliability, and edge cases, where applicable. Experience mentoring QA engineers and providing technical leadership across distributed and cross-functional teams. Strong collaboration skills with Development, Product, Architecture, DevOps, and Business teams. Excellent technical communication skills with the ability to communicate effectively with technical and non-technical stakeholders. Strong analytical and problem-solving skills with the ability to identify root causes, assess impact, define action plans, and drive issues to closure. Experience delivering quality solutions in financial/banking applications is preferred. Strong attention to detail and ability to work effectively in a dynamic, fast-paced environment.