We are looking for a dedicated QA Engineer to ensure the quality, performance, reliability, and compliance of solutions built with Microsoft Power Platform and Copilot Studio. This role involves leading test planning and execution for low-code applications, automated workflows, APIs, and conversational AI.

You will collaborate closely with developers, data engineers, data scientists, and business stakeholders to deliver high-quality solutions. A key focus will be on testing integrations and AI/ML-enabled features, ensuring seamless data flow and accurate outputs.

This hybrid position based in Bengaluru offers a unique opportunity to work on cutting-edge Microsoft technologies and contribute to innovative solutions.

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 Software Development Life Cycle.

Perform various types of testing, including functional, smoke, regression, integration, and end-to-end testing. Validate Dataverse tables, Power Automate flows, relationships, security roles, and data integrity rules. Design and execute conversation test scenarios for multi-turn context, ambiguity handling, and error recovery.

Conduct API testing for REST services and Azure ML endpoints using tools like Postman. Test data integrations involving Azure Databricks and Azure Storage. Plan and execute performance and load tests for workflows and APIs using JMeter. Identify, document, and track defects using Azure DevOps or Jira, and communicate test status, risks, and release readiness to stakeholders.

Requires 5-10 years of total experience, with a strong background in QA and testing. Must have 1-2 years specifically testing Microsoft Power Platform solutions, including hands-on experience with Power Automate workflows and data-centric applications.

Proficiency in Dataverse, connectors, Azure Databricks, and Azure Storage is essential. Familiarity with Copilot Studio or chatbot testing methodologies, including NLU and multi-turn flows, is required. Strong understanding of software testing principles, including test design, execution, and defect lifecycle, is a must.

Experience with API testing using Postman and performance testing using JMeter is critical. Ability to validate AI/ML outputs and collaborate with data teams is expected. Experience in developing and maintaining automation scripts for API, regression, and chat flow validation is preferred.