Abdul Aulleem

QA Engineer (Manual & Automation)

Bangalore 2+ yrs exp 89 · Excellent

About

QA Engineer with 2+ years of experience in both Manual and Automation Testing, specializing in functional, regression, and UAT validation for telecom applications. Strong expertise in test design, defect lifecycle, and Agile QA processes. Recently upskilled in GenAI-powered QA workflows, AI Agents, and tools like Copilot and Claude for test generation, debugging, and productivity acceleration.

Skills & Expertise (18)

AI-Assisted Test Case Generation Advanced

8.5/10

2.2

Years Exp

Selenium WebDriver Advanced

8.1/10

2.2

Years Exp

Pytest framework Advanced

7.9/10

2.2

Years Exp

Playwright SQL Jenkins Zephyr Scale Jira Python Page Object Model (POM Functional Testing Postman Test Case Design UAT Exploratory Testing sanity testing smoke testing Regression Testing

Work Experience

QA Automation Engineer

Revature Consultancy Services

Dec 2023 - Jan 2026

Performed manual, regression, and re-testing across releases to assure story readiness and release quality, supporting on-time release commitments by 90% - 95%. Managed JIRA workflows for defect logging, prioritization, and tracking, enforcing clear severity and priority to reduce reopen rates. Contributed in Agile ceremonies (stand-ups, planning, retrospectives) to align scope, surface risks early, and refine test plans. Partnered with distributed dev and QA peers to clarify acceptance criteria and ensure testability across multiple telecom applications. Led User Acceptance Testing (UAT) to validate business and functional requirements. Authored and executed test cases mapped to user stories in Zephyr Scale. Identified critical defects early, reducing downstream production issues. Coordinated closely with product owners and business stakeholders for requirement clarification. Participated in weekly client meetings, providing test insights, Demos and sprint feedback. Executed Python-based automation with Selenium and Playwright to expand regression coverage and reliability, reducing run time by 30% - 40%. Implemented a Hybrid Automation Framework with Pytest and POM, enabling data-driven tests and scaling suites to 60 test cases across modules. Produced Pytest HTML reports with screenshots to enhance defect visibility and accelerate triage, shortening turnaround time by 15%. Leveraged GitHub Copilot and Claude AI to accelerate test case creation, debugging, and automation scripting. Used GenAI tools to generate test scenarios, edge cases, and negative test data, improving test coverage. Applied prompt engineering techniques to refine AI-generated outputs for QA use cases. Built AI-assisted workflows to optimize regression test design and reduce manual effort. Utilized AI tools for faster defect analysis, log interpretation, and root cause identification. Explored AI Agents for QA automation support, improving productivity in repetitive testing tasks.