Join our dynamic team as a QA Engineer, focusing on ensuring the highest quality for solutions built on Microsoft Power Platform and Copilot Studio. This role is crucial for validating the performance, reliability, and compliance of cutting-edge data integrations and AI/ML-driven features.

You will lead test strategy and execution for a variety of components, including low-code applications, automated workflows, APIs, and conversational AI experiences. Close collaboration with developers, data scientists, and business stakeholders will be key to success in this hybrid role.

Define and implement comprehensive QA strategies and test approaches for Power Platform and Copilot Studio solutions.

Develop, review, and execute detailed test plans, test cases, and scripts throughout the Software Development Life Cycle (SDLC).

Conduct thorough functional, smoke, regression, integration, and end-to-end testing to identify and resolve issues.

Validate critical components such as Dataverse/Databricks tables, Power Automate flows, relationships, security roles, and data integrity.

Design and execute complex conversational AI test scenarios, focusing on multi-turn context, ambiguity handling, and error recovery mechanisms.

Perform API testing for REST services and Azure ML endpoints using tools like Postman and JMeter, and test data integrations involving Azure Databricks and Azure Storage.

Plan and conduct performance and load tests to ensure optimal workflow and API performance, generating detailed reports using JMeter.

Identify, document, and track defects meticulously using tools like Azure DevOps or Jira, ensuring clear communication of test status and risks to stakeholders.

We are seeking an experienced QA professional with a minimum of 3 years in testing, including 1-2 years specifically with Microsoft Power Platform solutions.

Demonstrated hands-on experience testing Power Automate workflows and data-centric applications is essential.

Familiarity with Dataverse, connectors, Azure Databricks, and Azure Storage is required.

Experience with chatbot testing methodologies and API testing using Postman or scripted validation (Python preferred) is necessary.

Proven ability in performance testing with JMeter or LoadRunner, including analysis and reporting, is crucial for this role.

Candidates should possess a solid understanding of software testing principles, defect lifecycle management, and the ability to validate AI/ML outputs.