Lead Quality Engineer

About the Role: Responsive is looking for a Quality Engineering (QE) Lead to drive end-to-end quality assurance and ensure the delivery of high-quality products . You will lead the QE team, implement automation strategies, and enhance testing processes while collaborating with cross-functional teams in an Agile environment . What You'll Be Doing Team Leadership & Strategy: Lead, mentor, and manage the QE team, setting goals and ensuring alignment with business objectives. Test Planning & Execution: Define QE strategies, oversee test case design, manage test execution (functional, regression, non-functional, exploratory), and ensure risk-based coverage. Automation & Performance Testing: Develop and maintain automation frameworks for functional, API, and performance testing (Playwright, Karate, JMeter). Drive test automation integration in CI/CD pipelines. Defect Management & Process Improvement: Oversee defect tracking, conduct root cause analysis, and enhance testing processes using best practices. Collaboration & Agile Practices: Work closely with product, development, and DevOps teams to establish quality goals, optimize testing strategies, and participate in Agile ceremonies. What We're Looking For Education: Bachelor's degree in Computer Science, IT, or related field. Experience: 8+ of experience in software quality engineering, with 1-2 years of leadership experience . Skills, Qualifications & Ability: Strong hands-on experience in UI automation, API testing, performance testing, and quality engineering. Expertise in building and maintaining scalable test automation frameworks. Proficiency with Playwright, Karate, JMeter, Postman, and similar testing tools. Strong programming skills in TypeScript, JavaScript, or Python. Experience with BDD frameworks and best practices. Hands-on experience integrating automation with CI/CD pipelines (Jenkins, GitHub Actions, or similar). Experience working in Agile environments and cloud-based testing. Familiarity with test management, reporting dashboards, and quality metrics. Understanding of AI concepts, AI-powered applications, AI testing, evaluation methodologies, and RAG fundamentals. Experience using AI-assisted engineering tools such as Cursor AI, GitHub Copilot, or similar. Excellent communication, problem-solving, and stakeholder management skills. Experience with SaaS or B2B products is an added advantage.