QA/QC Engineer

We are looking for a QA/QC Engineer with a strong background in application and digital project testing. The ideal candidate will have solid experience across functional and integration testing, with good exposure to AI, automation, and emerging technology projects.

The role will be responsible for ensuring the quality, reliability, and performance of digital solutions, including testing workflows, system integrations, APIs, automation processes, and AI-enabled use cases.

Key Responsibilities

• Plan, design, and execute QA/QC activities across application and digital projects.
• Develop and maintain test plans, test scenarios, test cases, and test scripts.
• Perform functional, regression, integration, system, and end-to-end testing.
• Test workflows, business processes, APIs, system integrations, and data flows.
• Validate automation solutions and ensure automated workflows perform as expected.
• Support testing of AI-enabled features and use cases, including AI-driven workflows and intelligent automation.
• Validate AI outputs against defined business requirements and expected results.
• Identify, document, track, and follow up on defects through resolution.
• Work closely with developers, business analysts, project managers, and technical teams to investigate and resolve issues.
• Perform root-cause analysis for recurring or critical defects.
• Verify fixes and conduct regression testing before releases.
• Support UAT activities and coordinate with business users to ensure requirements are properly validated.
• Review requirements and specifications to identify potential quality and testing risks early in the project lifecycle.
• Prepare QA status reports, defect reports, test execution reports, and quality metrics.
• Ensure solutions meet agreed quality, functionality, security, and performance requirements.
• Contribute to continuous improvement of QA processes, standards, and testing methodologies.

AI & Automation Testing

The candidate should have good exposure to testing technology-driven solutions, including:

• AI-enabled applications and business use cases.
• Generative AI or AI-assisted workflows.
• Automated business processes and workflows.
• API and system integration testing.
• Validation of AI-generated outputs against expected business outcomes.
• Data validation and consistency across integrated systems.
• Testing of end-to-end automated processes.
• Identifying edge cases and potential failure scenarios in AI/automation solutions.