Hands-on use of GenAI/AI tools (2 tools are must :GitHub CoPilot, ChatGPT, Cursor, Claude, Gemini) for software testing requirements analysis, test scenario identification, test-case generation, test-data

Understanding of LLMs, tokens/context windows, hallucinations, temperature, grounding and prompt/context management Ability to develop and maintain automation with AI assistance (Playwright with MCP, Selenium with MCP Tosca, Karate, REST Assured).

Experience in connecting to MCP server. TypeScript/JavaScript, Java or Python; ability to understand, review, debug and enhance AI-generated code Ability to critically review AI-generated test cases/code for correctness, coverage, hallucinations, security concerns and maintainability rather than accepting generated output blindly Integration and execution of automated tests through Jenkins, GitHub Actions, Azure DevOps or equivalent using AI tools Exposure to testing chatbots, copilots and GenAI applicationsincluding response quality, hallucination, groundedness and safety AWS, Azure or GCP (any 1) Jira, Azure DevOps, Xray, Zephyr or equivalent (any 1) Basic understanding of Retrieval-Augmented Generation and using enterprise knowledge/context with LLMs

📌 AI QE Engineer-Senior Manager (Bengaluru)
🏢 PwC
📍 Bengaluru