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The ideal candidate will combine strong software engineering and test automation expertise with practical knowledge of Artificial Intelligence (AI), Generative AI, and Large Language Models (LLMs) to design, develop, and implement next-generation automation frameworks.\nThe candidate will be responsible for building scalable, reusable, and intelligent automation solutions that integrate Python-based automation frameworks with Robot Framework and AI-powered capabilities. This role requires a strong understanding of automation architecture, API and UI testing, AI/LLM integration, CI/CD pipelines, and enterprise application ecosystems.\nThe ideal candidate should be comfortable translating complex business and technical requirements into reliable, maintainable, and AI-driven automation solutions.\n\nRequired Skills and Qualifications\n8+ years of overall experience in software engineering, test automation, quality engineering, or automation development.\nStrong hands-on expertise in Python programming and Robot Framework, with demonstrated experience combining both technologies in real-world projects.\nProven experience developing custom Python libraries and integrating them with Robot Framework.\nStrong understanding of object-oriented programming, data structures, exception handling, debugging, and software design principles.\nExperience developing and maintaining reusable automation frameworks.\nHands-on experience with API automation, REST services, JSON, HTTP protocols, and authentication mechanisms.\nExperience with UI automation using Selenium, Browser Library, or equivalent tools.\nPractical exposure to Generative AI, LLM APIs, prompt engineering, or AI-assisted automation.\nExperience with Git, CI/CD tools, automated test reporting, and build pipeline integration.\nGood understanding of SQL databases, test data management, and system integration.\nStrong analytical, troubleshooting, communication, and problem-solving skills.\n\nPreferred Skills\nExperience with AI frameworks and libraries such as LangChain, LlamaIndex, or comparable tools.\nExposure to AI agents, tool calling, Retrieval-Augmented Generation (RAG), and workflow orchestration.\nExperience with commercial or open-source LLMs and embedding models.\nFamiliarity with cloud platforms such as AWS, Azure, or Google Cloud.\nExperience with Docker, Kubernetes, and distributed automation execution.\nKnowledge of observability, structured logging, monitoring, and 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