Job Summary

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We are looking for a QA Engineer with 2+ years of experience with strong knowledge of SDLC/STLC, test execution, defect management, test automation, and QA delivery. The candidate should demonstrate strong ownership, effective cross-functional collaboration, and the ability to leverage AI tools to improve QA efficiency and productivity.

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Key Responsibilities

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Apply strong knowledge of SDLC/STLC, test planning, test case design, execution, and defect lifecycle.
Perform Unit, Integration, Functional, End-to-End (E2E), Regression, Smoke, Sanity, and Non-Functional testing.
Take end-to-end ownership of QA delivery, ensuring testing activities are completed within timelines and quality expectations.
Collaborate closely with developers to identify, reproduce, track, retest, and close defects.
Communicate testing status, risks, blockers, and delivery impact to relevant stakeholders.
Develop and maintain automated test scripts using Selenium and/or Playwright.
Leverage AI tools for test case generation, automation, test data creation, defect analysis, documentation, and other QA productivity improvements.
Participate in Agile ceremonies and collaborate effectively with Product, Development, and Business teams.
Support production issue analysis, RCA, and preventive QA measures.

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Required Skills

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2+ years of experience in Software QA/Testing.
Strong understanding of SDLC, STLC, and defect management.
Strong ownership and accountability for QA delivery.
Good communication, analytical, and cross-functional collaboration skills.
Hands-on knowledge of Selenium and/or Playwright.
Good understanding of functional and non-functional testing methodologies.
Basic knowledge of API testing and SQL.
Experience with Jira, Azure DevOps, or similar defect-tracking tools.
Experience using AI-powered tools to improve QA efficiency and automation.
Experience working on AI/Agentic AI, RPA, or Document Automation projects.

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Must Should Have this

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Practical knowledge of AI-assisted QA tools and prompt testing.
Basic understanding of AI Knowledge Bases (KB), RAG, retrieval, grounding, and hallucination testing.
Ability to design AI-specific test scenarios and evaluate AI-generated responses.
Experience working on AI/Agentic AI, RPA, or Document Automation projects.
Experience testing AI Agents, LLM-based applications, RAG pipelines, or AI-powered business workflows.

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