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Job Description & Summary: We are seeking an AI Test Automation Engineer with proven expertise in automation frameworks and a strong understanding of Artificial Intelligence (AI), Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI systems. 

The ideal candidate will be responsible for building AI-powered agents and automation solutions that accelerate Quality Assurance (QA) workflows. This includes developing intelligent systems capable of self-driven test case generation, defect triage, validation, and data-driven decision-making. 

This role blends core automation engineering with AI innovation and is ideal for professionals who want to push the boundaries of AI-assisted testing and autonomous QA systems. 

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 Why Join Us 

Join a forward-looking Quality Engineering team driving the transformation from automation to intelligence. As an AI Test Automation Engineer, you’ll help shape the future of Agentic QA, designing systems that learn, reason, and self-optimize — setting new standards for speed, precision, and innovation in software testing. 

Responsibilities: 

· Design and develop AI-driven QA agents using frameworks such as LangChain, AutoGen, LlamaIndex, or Semantic Kernel to automate validation and test execution workflows. 

· Build intelligent automation pipelines capable of reasoning over structured and unstructured data to support QA activities. 

· Develop RAG-enabled test agents that retrieve and contextualize test assets, requirements, and historical defects for intelligent recommendations. 

· Integrate LLMs and AI models with automation frameworks to enable adaptive test generation, self-healing scripts, and context-aware validation. 

· Design modular automation frameworks using Selenium WebDriver, Playwright, or Cypress in Python, Java, or C#. 

· Collaborate with AI and DevOps teams to operationalize Agentic QA workflows within CI/CD pipelines. 

· Validate LLM outputs for accuracy, grounding, and factual consistency, ensuring high-quality AI behavior in production environments. 

· Perform data validation and testing across structured (SQL, relational) and unstructured (NoSQL, vector DBs) databases. 

· Contribute to AI Quality Engineering accelerators and internal innovation initiatives within the Test CoE. 

Mandatory skill sets: 

• · Strong programming skills in Python, with exposure to AI libraries and frameworks (LangChain, LlamaIndex, OpenAI APIs). 

• · Good understanding of LLM architectures, RAG pipelines, and Agentic AI concepts (task orchestration, reasoning loops, and autonomy). 

• · Experience integrating with vector databases (Pinecone, Weaviate, FAISS, Chroma) and cloud data stores. 

• · Familiarity with DevOps and CI/CD ecosystems (Jenkins, GitHub Actions, Azure DevOps). 

• · Strong problem-solving and analytical skills with a passion for AI-driven quality engineering. 

• · Proficiency in test automation tools (Selenium, Playwright, Cypress) and frameworks (TestNG, PyTest, Cucumber). 

• · Excellent communication skills and ability to collaborate across Agile teams. 

Preferred skill sets: 

· Understanding of Responsible AI principles and model interpretability practices. 

· Prior work building custom AI agents or copilots for QA, automation, or DevOps use cases. 

· Certifications in AI/ML, Test Automation, or Cloud Technologies. 

Years of experience required: 

2 to 4 years..Years of Experience in software automation QA … Minimum 1+ year experience in AI , LangChain, LlamaIndex, OpenAI APIs or AI agents. 

Education qualification: 

B.E. / B.Tech / MCA/ M.E/ M.TECH/ MBA/ PGDM. All qualifications should be in regular full-time mode with no extension of course duration due to backlogs