Senior Software QA Engineer

• Define and execute the AI-based QA strategy across projects.

• Design and develop scalable AI-enabled automation frameworks.

• Implement AI/GenAI use cases such as:

• Test case & script generation

• Defect analysis & prediction

• Risk-based and intelligent testing

• Test data generation

• Build self-healing automation, smart reporting, and predictive analytics solutions.

• Evaluate and integrate AI tools, LLMs, and QA platforms.

• Collaborate with cross-functional teams (QA, Dev, Product, DevOps).

• Establish best practices, governance, and reusable QA components.

• Develop POCs and scale them to enterprise-level solutions.

• Define and track automation and AI effectiveness metrics.

• Mentor teams on AI-driven QA practices.

Education

• 10+ years in QA, automation, or architecture roles.

• Strong experience in test automation frameworks (Selenium, Playwright, Cypress, Appium, REST Assured, etc.).

• Solid understanding of AI/ML/GenAI concepts applied to QA.

• Hands-on experience with LLM-based solutions (test generation, log analysis, etc.).

• Programming expertise in Python, Java, or JavaScript.

• Experience with CI/CD tools (Jenkins, GitHub Actions, Azure DevOps, etc.).

• Knowledge of API, UI, performance, security testing, and test data management.

• Ability to design and integrate AI-first QA solutions.

• Strong architecture, problem-solving, and stakeholder management skills.

Preferred:

• GenAI, prompt engineering, RAG, AI agents

• MLOps / LLMOps knowledge

• Cloud (AWS/Azure/GCP)

• Vector DBs, embeddings, AI orchestration

  • Predictive analytics & self-healing automation