Role Overview :

We are looking for an experienced and technically strong QA Manager with 13+ years of experience in software quality assurance, test automation, and quality engineering. The ideal candidate should have strong hands-on expertise in Automation Testing and practical experience working with AI/Generative AI technologies in software testing or quality engineering. The candidate will be responsible for defining QA strategy, driving automation initiatives, improving test coverage, and leading the adoption of AI-driven testing practices.

Responsibilities :

- Define and implement the overall QA and Quality Engineering strategy across products and applications.
- Lead and mentor QA engineers, automation engineers, and SDET teams.
- Drive the design, development, and maintenance of robust test automation frameworks.
- Establish automation standards, best practices, coding guidelines, and reusable testing components.
- Identify opportunities to increase automation coverage and reduce manual testing efforts.
- Design and execute strategies for functional, regression, integration, API, UI, performance, and end-to-end testing.
- Integrate automated testing into CI/CD pipelines and support continuous quality practices.
- Work closely with Engineering, Product, DevOps, and other stakeholders to ensure quality throughout the SDLC.
- Define QA metrics, quality gates, test coverage, defect leakage, automation coverage, and release-quality KPIs.
- Drive root-cause analysis of critical production defects and implement preventive quality measures.
- Evaluate and introduce contemporary testing tools, frameworks, and methodologies.
- Lead the adoption of AI/Generative AI in Software Testing, including AI-assisted test generation, test-case optimisation, defect analysis, test-data generation, and intelligent automation.
- Explore and implement AI-powered testing tools and solutions to improve QA productivity and test effectiveness.
- Evaluate the use of LLMs, AI agents, and AI-assisted development/testing workflows within the QA lifecycle.




- Establish best practices for testing AI/ML-based applications where applicable.
- Ensure adequate test planning, risk assessment, release readiness, and quality governance.
- Collaborate with engineering leadership to improve overall software reliability and engineering quality.

Leadership Responsibilities :

- Lead and develop a high-performing QA/Quality Engineering team.
- Set technical direction for automation and AI-driven testing.
- Conduct technical reviews and establish engineering best practices.
- Mentor senior QA engineers and automation specialists.
- Define team objectives, delivery expectations, and quality standards.
- Partner with senior engineering and product leadership on quality initiatives.
- Drive continuous improvement across the QA organisation.

Mandatory Technical Skills :

Automation Testing :

- Strong hands-on experience in Test Automation and designing scalable automation frameworks.
- Proficiency in tools/frameworks : Selenium, Playwright / Cypress, Appium, REST Assured / API Automation, PyTest / JUnit / TestNG.
- Strong programming experience in Java, Python, JavaScript, or similar languages.

AI/GenAI :

- Practical exposure to AI/Generative AI in QA, including AI-assisted test-case generation, LLM-based testing solutions, AI-powered defect analysis, and AI agents for QA workflows.

CI/CD and DevOps :

- Strong understanding of CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI/CD, Azure DevOps).
- Experience integrating automated test suites into CI/CD pipelines.

Additional Skills :

- Strong understanding of Agile/Scrum methodologies.
- Experience with defect-management and test-management tools (Jira, Azure DevOps, Zephyr, TestRail).
- Strong analytical, problem-solving, and stakeholder-management skills.

Key Success Metrics :

- Automation coverage and reliability.
- Reduction in regression-testing effort.
- Defect detection and prevention.
- Production defect leakage.
- Test execution efficiency.
- CI/CD quality-gate adoption.
- Release quality and stability.
- Adoption and measurable impact of AI-driven testing initiatives.

📌 Quality Assurance Manager - Automation Testing (India)
🏢 Bulwark Software Research
📍 India