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, Mule Soft, 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.

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• 3+ years of QA, test automation, or software testing experience
• Hands on experience building automated tests (Selenium, Playwright, Cypress, Jest, Pytest, etc.)
• Ability to write scripts/code in Python, JavaScript, Java, or C#
• Experience testing APIs and integrations
• Strong understanding of Agile/Scrum practices
• Experience using defect and test management tools (Jira, Azure Dev Ops, Test Rail, etc.)
• Excellent communication and documentation skills
• Strong attention to detail, analytical thinking, and ability to identify edge cases
• AI/ML testing experience:
  Familiarity with testing AI models, LLMs, chatbots, or machine learning systems including validation of AI outputs for accuracy, bias, and hallucinations.
• Salesforce testing knowledge:
  Understanding of Salesforce platform, data model, and testing approaches for Salesforce applications and customizations.
• API and integration testing:
  Experience testing APIs, web services, and integration platforms like Mule Soft, including REST/SOAP protocols and data validation.
• CI/CD pipeline experience:
  Familiarity with integrating automated tests into CI/CD pipelines using tools like Jenkins, Git Hub Actions, Git Lab CI, or Azure Dev Ops.
• Performance and load testing:
  Experience with performance testing tools such as JMeter, Load Runner, or k6 for validating system scalability and reliability.
• GenAI fluency:
  Comfort using generative AI tools (ChatGPT, Claude, etc.) to streamline test case generation, test data creation, and documentation.
• Database and SQL knowledge:
  Ability to write SQL queries for data validation, test data setup, and database testing.