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.
