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Mid-level QA automation role, popular title, metro location and funded startup amplify applicant competition.
Automation skills transferable, but AI/data-pipeline focus raises moderate industry specificity.
Explicit 5+ years requirement plus enterprise data and automation experience filters candidates.
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Design and implement automated test frameworks for AI, data, and application workflows ensuring system robustness and reliability.
Validate end-to-end AI pipelines including data ingestion, model inference, and output accuracy, consistency, and regression detection.
Collaborate with engineering teams to monitor system health, identify quality risks, and improve testability and overall product quality.
Bachelor’s degree in Computer Science, Engineering, or related field.
Minimum 5 years of experience in QA, automation, or software testing, including enterprise-scale or data-intensive applications.
Strong experience in test automation, quality engineering, API testing, backend validation, and scripting languages such as Python.
Familiarity with CI/CD pipelines and automated testing integrations; exposure to AI, ML, or analytics systems is a plus.
Experienced professional comfortable working on AI-driven, data-intensive systems with focus on automated testing quality and reliability.
Operates strategically with ownership mindset, showing capability to define quality metrics and drive quality improvement collaboratively.
Background in developing and maintaining automated test suites within an enterprise SaaS environment involving complex AI and data workflows.