Senior Software QA Engineer

Job Summary Lead the design and implementation of an AI-driven QA strategy to transform testing processes. Architect and build next-generation QA frameworks leveraging AI/ML and Generative AI. Drive innovation across test automation, defect prediction, and test optimization to improve quality, efficiency, and speed. Act as a technical leader and advisor, enabling teams to adopt AI-powered testing solutions at scale. Job Requirements 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