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AI Tester

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Dallas, TX, United States Macpower Digital Assets Edge Full time
Job Summary: We are seeking a highly skilled Senior QA Automation Engineer with 6+ years of experience in Software Functional Testing and 4-7 years of expertise in Selenium. The ideal candidate will lead system integration testing, ensure adherence to quality standards, and develop AI-specific automated testing frameworks. This role requires expertise in Agile methodologies, test automation tools, and AI model evaluation using LLMs and RAG architectures.
Key Responsibilities:
  • Conduct system integration testing for new and enhanced applications.
  • Develop and execute automated tests using Selenium and other industry-standard tools.
  • Collaborate with project teams to establish plans, standards, and procedures that optimize testing efforts.
  • Ensure on-time delivery by monitoring dependencies, progress, and milestones.
  • Educate business and development teams on the testing methodology, with a focus on end-to-end quality assurance.
  • Lead project and quality management initiatives, including issue tracking and communication.
  • Optimize resource utilization by assisting the Testing Manager in reviewing forecasting reports.
  • Ensure compliance with Agile methodologies, maintaining detailed process documentation.
  • Perform AI-specific testing, including validation of LLMs and RAG architectures using vector databases.
  • Implement automated testing frameworks for Gen AI applications, such as DeepEval and RAGAs.
  • Develop custom validation scripts for evaluating AI model accuracy, relevance, and faithfulness.
  • Test prompt engineering techniques to refine AI-generated responses.
  • Execute SQL queries in Snowflake to validate database integrity and application responses.
Essential Skills & Experience:
  • 6+ years of experience in Software Functional Testing with automation expertise in Selenium.
  • Experience with Jira and ALM for test and issue tracking.
  • Strong proficiency in Python, with experience in AI testing frameworks such as LangChain, Pytest, and PyTorch.
  • Hands-on expertise in LLM & RAG architecture testing using vector databases.
  • Familiarity with Snowflake, SQL querying, and data validation techniques.
  • Excellent communication and leadership skills to engage with stakeholders.