Legrand has an exciting opportunity for a QA Software Engineer to join the Power and Thermal Management Division in Bengaluru, Karnataka/India . As a QA Software Engineer, you will be responsible for ensuring the quality, reliability, and performance of our software products through manual and automated testing. You will create and maintain test plans, test cases, automation scripts, and defect reports, while collaborating closely with Software Engineering, Product Management, and other QA team members throughout the development lifecycle.
You will also contribute to test automation strategy, analyze automated test results, troubleshoot failures, and participate in technical and architecture discussions. AI-assisted engineering tools will be an important part of the role, supporting activities such as test design, automation development, debugging, defect investigation, and continuous improvement of QA processes.
Responsibilities
Design, maintain, and execute test plans, test cases, and test scenarios.
Develop and maintain automated test scripts for functional, regression, integration, and end-to-end testing.
Identify opportunities to increase automation coverage and reduce repetitive manual testing.
Perform functional, regression, integration, exploratory, negative, boundary, compatibility, and system testing.
Identify, reproduce, document, and track software defects throughout their lifecycle.
Analyze automated test results, logs, and failures to identify product, automation, or environment issues.
Debug and troubleshoot network protocols, APIs, services, and system behavior.
Maintain clear and accurate QA documentation.
Collaborate with Software Engineering, Product Management, and QA teams throughout the development lifecycle.
Participate in technical, design, architecture, and code review discussions from a quality and testability perspective.
Integrate and maintain automated tests within CI/CD pipelines.
Use AI-assisted tools to support test case generation, automation development, debugging, log analysis, defect investigation, and technical documentation.
Identify opportunities to apply AI and automation to improve test efficiency, coverage, reliability, and overall QA productivity.
Contribute to the continuous improvement of QA processes, tools, automation frameworks, and engineering practices.
Qualifications
Bachelor’s degree in Engineering, Computer Science, Information Technology, or a related field.
4+ years of professional experience in Software QA, Software Testing, or a related engineering role.
Strong understanding of Software QA methodologies, testing techniques, and Agile software development practices.
Experience creating and executing both manual and automated test cases.
Experience with functional, regression, integration, negative, boundary, compatibility, and concurrency testing.
Experience developing, maintaining, or contributing to automated test frameworks.
Experience working with CI/CD environments and automated test execution pipelines.
Practical experience using AI-assisted engineering tools such as GitHub Copilot, ChatGPT, Claude, Gemini, or similar technologies for testing, automation, debugging, or technical analysis.
Skills/Knowledge/Abilities:
Strong analytical, troubleshooting, and problem-solving skills.
Excellent written and verbal communication skills in English.
Strong experience with test automation tools and frameworks such as Robot Framework, Selenium, Cypress, Playwright, or similar technologies.
Experience developing, maintaining, and troubleshooting automated test suites.
Ability to identify suitable automation candidates and improve regression and end-to-end test coverage.
Experience with CI/CD tools and practices, such as Jenkins, GitLab CI/CD, GitHub Actions, or similar platforms.
Experience with Git, GitLab, GitHub, and standard code review workflows.
Strong scripting or programming skills in Python are required. Experience with Golang or Java is a plus.
Basic knowledge of networking, APIs, web services, and distributed systems.
Practical knowledge of Generative AI and AI-assisted software engineering tools.
Ability to use AI effectively for test generation, automation development, test data creation, debugging, log analysis, and defect investigation.
Ability to critically review and validate AI-generated code, scripts, test cases, and technical recommendations.
Familiarity with prompt engineering and providing appropriate technical context to AI tools.
Interest in applying AI to areas such as automation maintenance, failure analysis, test optimization, and defect classification.
Experience testing AI-enabled applications or features is considered a plus.
Strong attention to detail and ability to clearly document test results, defects, and technical findings.
Strong interest in continuously improving QA practices, automation coverage, engineering efficiency, and software quality.
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