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3–5+ years of experience in Quality Engineering, Quality Assurance, or Software Testing, including 3+ years in test automation development and 2+ years testing AI, machine learning, Generative AI, LLM, or intelligent automation solutions.
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Strong experience designing automated test frameworks, validating AI-generated outputs, and performing API, integration, and data testing.
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Proficiency in Python, Java, or similar programming languages, with solid knowledge of Agile, SDLC, CI/CD, and Responsible AI principles, including fairness, bias detection, transparency, explainability, and human oversight. Strong analytical, communication, and cross-functional collaboration skills are required.
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Experience testing RAG pipelines, chatbots, conversational AI, AI agents, and LLM-based applications, including hallucination detection, prompt robustness, model drift, bias, and adversarial testing.
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Knowledge of AI evaluation frameworks, test harnesses, MLOps, AI governance, and cloud platforms such as Azure, AWS, or Google Cloud Platform.
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Experience within healthcare, payer, provider, pharmacy, claims, or other regulated environments is preferred.
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Familiarity with accessibility testing, audit and compliance processes, and mentoring QA engineers is a plus.
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AI Tool Expectations: Consistent use of enterprise-approved AI tools, including GitHub Copilot and Microsoft 365 Copilot, targeting a minimum of 90% weekly utilization to enhance testing, documentation, analysis, and delivery efficiency.
