QA Engineer (AI/Automation Validation)

Job Description The QA Engineer (AI/Automation Validation) ensures the quality, reliability, and safety of the company's AI agents and automation workflows across Salesforce, MuleSoft, and AI platforms. This role designs and executes test strategies, builds automated testing frameworks, validates AI outputs for accuracy and consistency, and tests how systems integrate and exchange data. The engineer partners closely with developers, business analysts, and project managers to identify defects, test edge cases, document results, and provide the final quality sign off before production releases. They maintain test assets, support Agile ceremonies, and continuously improve testing processes to ensure stable, high quality AI and automation solutions. We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: Skills and Requirements u2022 3+ years of QA, test automation, or software testing experience u2022 Hands on experience building automated tests (Selenium, Playwright, Cypress, Jest, Pytest, etc.) u2022 Ability to write scripts/code in Python, JavaScript, Java, or C# u2022 Experience testing APIs and integrations u2022 Strong understanding of Agile/Scrum practices u2022 Experience using defect and test management tools (Jira, Azure DevOps, TestRail, etc.) u2022 Excellent communication and documentation skills u2022 Strong attention to detail, analytical thinking, and ability to identify edge cases u2022u2003AI/ML testing experience: Familiarity with testing AI models, LLMs, chatbots, or machine learning systems including validation of AI outputs for accuracy, bias, and hallucinations. u2022u2003Salesforce testing knowledge: Understanding of Salesforce platform, data model, and testing approaches for Salesforce applications and customizations. u2022u2003API and integration testing: Experience testing APIs, web services, and integration platforms like MuleSoft, including REST/SOAP protocols and data validation. u2022u2003CI/CD pipeline experience: Familiarity with integrating automated tests into CI/CD pipelines using tools like Jenkins, GitHub Actions, GitLab CI, or Azure DevOps. u2022u2003Performance and load testing: Experience with performance testing tools such as JMeter, LoadRunner, or k6 for validating system scalability and reliability. u2022u2003GenAI fluency: Comfort using generative AI tools (ChatGPT, Claude, etc.) to streamline test case generation, test data creation, and documentation. u2022u2003Database and SQL knowledge: Ability to write SQL queries for data validation, test data setup, and database testing.

Created: 2026-01-19