Seeking a meticulous QA Engineer to ensure the quality, performance, reliability, and compliance of solutions built on Microsoft Power Platform and Copilot Studio. This role involves leading test planning and execution for low-code applications, automated workflows, APIs, and conversational AI, in close collaboration with development teams, data scientists, and business stakeholders.

Key responsibilities include developing and maintaining QA strategies, creating and executing comprehensive test plans and cases, and performing various testing types such as functional, integration, and end-to-end. A strong focus will be placed on validating data integrations, AI/ML features, and conversational AI dialogues.

Define and execute comprehensive QA strategies and test plans for Power Platform and Copilot Studio solutions. Perform thorough functional, regression, integration, and end-to-end testing across the SDLC. Validate critical components like Dataverse, Power Automate flows, security roles, and data integrity. Design and execute intricate test scenarios for conversational AI, including context management and error handling. Conduct API testing for REST services and Azure ML endpoints using tools like Postman. Plan and execute performance and load tests, utilizing JMeter to simulate real-world traffic. Identify, document, and track defects diligently using Azure DevOps or Jira. Communicate test status, risks, and release readiness effectively to all stakeholders. Contribute to the development of QA best practices and automation frameworks.

A minimum of 9 years of QA experience, with at least 1-2 years specifically testing Microsoft Power Platform solutions, is essential. Candidates should possess hands-on experience with Power Automate workflows and data-centric applications, alongside a working knowledge of Dataverse, Azure Databricks, and Azure Storage.

Familiarity with Copilot Studio or chatbot testing methodologies, coupled with a strong grasp of software testing principles, is required. Experience in API testing using Postman and performance testing with JMeter or LoadRunner is crucial. The ability to validate AI/ML outputs and collaborate with data teams is also a key requirement. Proficiency in developing automation scripts for API and regression testing is highly valued.