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Popular mid-level QA role with generalist requirements and modest brand, resulting in moderate competition.
Core QA skills transferable, but AI/LLM testing specialization increases domain bias.
Explicit 1–3 years requirement plus mandatory QA skills and tools implies moderate filter strictness.
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Test modern web applications including frontend, backend, APIs, and user workflows for quality assurance.
Validate AI-powered products, agents, and workflows assessing output accuracy, consistency, and edge cases.
Leverage AI tools to generate test cases, enhance coverage, accelerate regression testing, and support automation of repetitive tests.
1-3 years of experience in manual and/or automation testing.
Hands-on experience testing web applications and APIs.
Experience using AI tools (e.g., ChatGPT, Claude, Gemini) specifically for QA purposes.
Familiarity with testing and project management tools such as Postman, Swagger, Jira, and basic automation tools like Selenium, Playwright, or Cypress.
Demonstrates advanced QA capabilities blending traditional software testing with AI-driven product validation.
Ability to think beyond standard happy-path scenarios and to identify complex edge cases and gaps in requirements.
Skilled at integrating AI-assisted testing to improve quality assurance efficiency and accuracy.