3 - 5 years of hands-on manual/functional QA experience across web, API, and mobile applications. Strong knowledge of software testing principles - test design techniques, defect lifecycle, and QA best practices. Experience with test planning, coverage analysis, and test execution across the full SDLC. Solid understanding of Agile/Scrum workflows and sprint participation. Hands-on experience testing AI/ML-based products or features - chatbots, recommendation engines, LLM-powered tools, or similar. Ability to design test scenarios for non-deterministic or AI-generated outputs using range-based and behaviour-based validation. Exposure to prompt testing and evaluating AI feature accuracy, relevance, and edge-case behaviour. Ability to design and execute detailed test cases covering functional, regression, integration, and UAT scenarios. Manual API testing using Postman - validating request/response, schema, auth flows, and error handling. Familiarity with mobile testing basics - device fragmentation, gestures, and cross-platform behaviour. Strong command of test documentation - test plans, test cases, and defect reports. Working exposure to automation tools such as Selenium, Playwright, or Cypress is a plus. Basic scripting knowledge in Python or JavaScript is beneficial but not required. Basic SQL for data validation, JIRA/Confluence for test management, and BDD (Cucumber/Gherkin) exposure is a plus. Exposure to cross-browser testing tools such as BrowserStack or Sauce Labs is beneficial. Detail-oriented and systematic - documents, reproduces, and communicates defects clearly and consistently. Strong collaborator who works naturally with developers, product managers, and AI/data teams. Self-starter with an ownership mindset - proactively identifies quality gaps. Curious about AI tools and product features, willing to learn and adapt testing approaches. Effective communicator who can explain test results, coverage, and release risk to stakeholders.