Join our team as a QA Engineer specializing in Functional and Automation testing, focusing on solutions built with Microsoft Power Platform and Copilot Studio. This hybrid role in Chennai is crucial for ensuring the quality, performance, and reliability of our innovative data integrations and AI/ML features. You will spearhead test planning and execution for low-code applications, automated workflows, APIs, and conversational AI, collaborating closely with developers, data scientists, and business stakeholders.

Define and maintain the QA strategy, test approach, and coverage for Power Platform and Copilot Studio solutions. Create, review, and execute comprehensive test plans, test cases, and scripts throughout the SDLC. Conduct functional, smoke, regression, integration, and end-to-end testing. Ensure complete traceability from requirements to defects and releases. Validate Dataverse/Databricks data, Power Automate flows, security roles, and data integrity. Design and execute conversation test scenarios for AI bots, including multi-turn context and error recovery. Perform regression testing for AI bot behavior changes. Conduct API testing for REST services and Azure ML endpoints using tools like Postman/JMeter. Test data integrations with Azure Databricks and Azure Storage. Plan and execute performance and load tests using JMeter. Identify, document, and track defects using Azure DevOps or Jira. Communicate test status, risks, and release readiness to stakeholders. Collaborate with teams to clarify requirements and contribute to QA best practices.

We are looking for a candidate with 3+ years of QA experience, including 1-2 years dedicated to testing Microsoft Power Platform solutions. Essential skills include hands-on experience with Power Automate workflows, data-centric applications, and familiarity with Dataverse, connectors, Azure Databricks, and Azure Storage. You should possess a strong understanding of software testing principles and experience with API testing using Postman. Performance testing expertise with JMeter or LoadRunner is required, along with the ability to validate AI/ML outputs and collaborate with data teams. Basic knowledge of prompt design for AI agent behavior and experience developing automation scripts for API, regression, and chatbot validation are key. Experience with pattern matching, similarity scoring, and semantic validation for chatbot responses is also important.