Automated Testing in Mobile

The successful candidate will be responsible for defining and executing the quality strategy, establishing QA best practices, mentoring team members, and ensuring the delivery of high-quality AI-powered solutions.

Key Requirements:

• 5+ years of hands-on automation testing experience, with proven expertise in designing, developing, and maintaining automated testing solutions.
• Demonstrated experience in a technical leadership or AQA Lead role, driving quality initiatives and automation strategy.
• Experience testing GenAI applications and familiarity with evaluation frameworks such as RAGAS.
• Proven ability to define and maintain QA strategies, test plans, automation roadmaps, and test execution frameworks.
• Strong experience building, enhancing, and maintaining test automation frameworks and automated test suites.
• Ability to review user stories, requirements, architecture designs, and data artifacts to ensure solutions meet business and end-user expectations.
• Hands-on experience designing comprehensive test scenarios, test cases, and automated validation approaches from requirements.
• Partner with development and product teams to define quality standards, provide test data, support POCs, and drive shift-left testing practices.
• Own and oversee end-to-end testing activities, including test execution, defect management, root-cause analysis, risk assessment, and quality reporting.
• Strong stakeholder management, communication, analytical, and problem-solving skills.
• Experience working within Agile teams and CI/CD-driven development environments.

Key Responsibilities:

• Lead the quality engineering and test automation strategy for AI-powered products and solutions.
• Establish and promote QA best practices, testing standards, and automation-first approaches across the POD.
• Mentor and provide technical leadership to QA and engineering team members.
• Actively contribute to automation framework development, code reviews, troubleshooting, and test implementation.
• Drive continuous improvements in automation coverage, test reliability, and release quality.
• Collaborate closely with Product Managers, Developers, Data Scientists, and Architects to embed quality throughout the software development lifecycle.
• Identify quality risks early and proactively drive mitigation actions.