Seeking a detail-oriented QA Engineer to ensure the quality, performance, and reliability of solutions built on Microsoft Power Platform and Copilot Studio. This role involves testing low-code applications, automated workflows, APIs, and conversational AI. You will collaborate closely with developers, data engineers, and business stakeholders to deliver robust and compliant solutions.

This hybrid position focuses on testing data integrations and AI/ML-enabled features. You'll lead test planning and execution, ensuring seamless integration of various components and adherence to quality standards.

Develop 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 test scripts throughout the SDLC.

Conduct functional, smoke, regression, integration, and end-to-end testing. Validate Dataverse/Databricks tables, Power Automate flows, relationships, and security roles. Design and execute conversation test scenarios for chatbots, ensuring effective handling of multi-turn context and error recovery. Perform API testing for REST services and Azure ML endpoints using tools like Postman and JMeter. Test data integrations and pipelines involving Azure Databricks and Azure Storage. Plan and execute performance and load tests, simulating real-world traffic and generating detailed reports. Identify, document, and track defects using Azure DevOps or Jira. Communicate test status, risks, and release readiness to stakeholders. Collaborate with product teams to clarify acceptance criteria and non-functional requirements. Contribute to QA best practices and automation frameworks.

A minimum of 3 years of QA/testing experience is required, with at least 1-2 years specifically testing Microsoft Power Platform solutions. You should have hands-on experience testing Power Automate workflows and data-centric applications.

Proficiency is expected in Dataverse, connectors, Azure Databricks, and Azure Storage. Familiarity with Copilot Studio or chatbot testing methodologies is essential. A strong understanding of software testing principles, including test design, execution, defect lifecycle, and reporting, is crucial. Experience with API testing using Postman and/or scripted validation (Python preferred) is required. Hands-on performance testing experience with JMeter or LoadRunner, including analysis and reporting, is necessary.

Demonstrated ability to validate AI/ML outputs and collaborate with data teams on statistical checks is important. Basic understanding of designing prompts and edge cases to evaluate AI agent behavior is beneficial. The role requires the ability to develop and maintain automation scripts for API testing, regression test suites, and chat flow validation, along with automated validation for chatbot responses.