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Remote and mid-level amplifiers present, but niche LLM QA reduces applicant density, yielding medium competition.
Specialized Conversational AI/LLM QA skills limit transferability, so background sensitivity is high.
Explicit 3–7 years plus mandatory Conversational AI/LLM QA experience and tools makes screening strict.
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Develop and execute comprehensive test cases and automation scripts for Conversational AI, Agentic AI, and LLM systems.
Lead defect identification, documentation, and tracking using JIRA, ensuring quality across the AI product lifecycle.
Collaborate with product managers and developers to design tailored QA strategies and generate detailed test reports for stakeholders.
3 to 7 years of experience in software testing and quality assurance specifically in Conversational AI and Agentic AI/LLMs.
Proven expertise in both manual and automation testing techniques.
Proficient in defect tracking using JIRA and data reporting using Excel.
Not explicitly mentioned in the JD: educational qualifications, notice period, or specific location constraints.
Experienced in testing complex AI systems with a focus on conversational platforms and large language models.
Skilled in cross-functional collaboration, working closely with technical and product teams in fast-paced environments.
Detail-oriented professional with strong analytical skills and familiarity with AI testing methodologies including functional, regression, integration, and performance testing.