Assistant Manager-GTS Build

Roles & responsibilities 
A detail-oriented and proactive QA Engineer with 3–5 years of experience in manual testing, automation testing, and AI-driven quality practices. The ideal candidate will be responsible for ensuring software quality across the testing lifecycle by designing test strategies, executing functional and non-functional testing, building and maintaining automation scripts, identifying defects early, and leveraging AI tools to improve test effectiveness, speed, and coverage.
This role requires strong collaboration with product owners, developers, and business stakeholders in an agile environment to deliver high-quality, scalable, and reliable solutions.

Responsibilities:
Analyze business requirements, user stories, and technical specifications to derive test scenarios, test cases, and validation approaches.
Prepare and execute manual test cases for functional, regression, integration, system, exploratory, UI, and end-to-end testing.
Design, develop, maintain, and execute automation test scripts/frameworks for web and/or API-based applications.
Participate in sprint planning, grooming, daily stand-ups, test estimation, and release validation activities.
Perform smoke, sanity, regression, and defect retesting to ensure release readiness.
Identify, log, track, and validate defects using tools such as Azure DevOps / JIRA and work closely with development teams for timely resolution.
Contribute to risk-based testing and ensure adequate test coverage for critical business flows.

Validate test data, environments, and integrations to support effective QA execution.
Prepare test status reports, execution summaries, and quality metrics for stakeholders.
Support AI-assisted testing by using AI tools to accelerate test case generation, defect analysis, test optimization, and productivity improvements.
Apply quality engineering best practices to improve automation coverage, reduce manual effort, and enhance release confidence.
Continuously identify opportunities to improve QA processes, standards, reusable assets, and overall engineering efficiency.
Exposure to cloud platforms such as Azure / AWS.
Experience in testing AI-enabled applications, copilots, LLM-based solutions, or conversational interfaces.
Awareness of prompt validation, response testing, output consistency, hallucination checks, and responsible AI testing concepts.
 

This role is for you if you have  the below
Educational qualifications

Bachelor’s degree in Computer Science, Information Technology, or related field

Work experience
6-8 Years of Experience