Quality Assurance Engineer

Manual Testing with Exposure to Automation, Performance Testing

Experience: 1 to 4 years

Role Overview

We are looking for a Quality Assurance Engineer with experience in manual software testing and an interest in modern quality engineering practices. You will review requirements, design and execute tests, identify defects, and collaborate with developers and product teams to ensure the delivery of high-quality software. The role primarily focuses on manual testing while providing opportunities to work with test automation, performance testing, and AI-powered testing tools to improve testing efficiency and coverage.

Key Responsibilities

• · Review business requirements, user stories, and system specifications to identify test scenarios, gaps, and acceptance criteria.

• · Prepare and maintain test plans, test cases, checklists, and test data covering positive, negative, boundary, and exploratory testing scenarios.

• · Execute functional, integration, system, smoke, sanity, regression, and exploratory testing; record results and supporting evidence.

• · Validate application behavior, usability, responsiveness, and compatibility across browsers, devices, and platforms.

• · Test REST APIs using Postman and validate backend data using SQL/NoSQL queries.

• · Log defects in Jira with clear reproduction steps, expected and actual results, severity, and supporting evidence; retest fixes and track defects to closure.

• · Collaborate with developers to reproduce and troubleshoot issues, assess impact, and prioritize testing activities.

• · Share test progress, coverage, defects, and release risks through clear test reports; raise blockers promptly.

• · Perform post-release verification and support User Acceptance Testing (UAT) when required.

• · Assist in creating, maintaining, and executing automated test scripts using tools such as Selenium, Playwright, Cypress, or similar frameworks.

• · Participate in basic load, stress, and performance testing activities using tools such as JMeter, k6, or equivalent tools.

• · Analyze application performance metrics and help identify bottlenecks affecting user experience and scalability.

• · Utilize AI-powered testing tools and Generative AI solutions to accelerate test case generation, test data creation, defect analysis, root cause investigation, and overall QA productivity.

• · Continuously evaluate opportunities to improve test coverage, efficiency, and software quality through automation and AI-assisted testing techniques.

• · Keep test documentation current as features and business requirements evolve.

• Requirements

• Bachelor’s degree in computer science, Information Technology, Computer Applications, or a related field.·

• 1 to 4 years of experience in software testing, quality assurance, or a similar QA role.

• Strong understanding of QA methodologies, SDLC, STLC, Agile development practices, and defect life cycle management.

• Ability to translate business requirements into comprehensive test cases and identify edge cases, risks, and validation scenarios.

• Hands-on experience with manual functional, regression, integration, and exploratory testing.

• Working knowledge of Postman for API testing, SQL/NoSQL for data validation, and Jira for defect management.

• Exposure to automation testing concepts and frameworks such as Selenium, Playwright, Cypress, or similar tools.

• Basic understanding of performance and load testing concepts and tools such as JMeter, k6, LoadRunner, or equivalent.

• Familiarity with AI-assisted testing tools, Generative AI platforms (such as GitHub Copilot, ChatGPT, Gemini, or similar), and their application in software testing activities.

• Familiarity with TestLink or similar test management tools for organizing test cases and recording execution results.

• Strong analytical, troubleshooting, and problem-solving skills with attention to detail.

• Excellent written and verbal communication skills and the ability to work effectively in a collaborative Agile environment.

Preferred Skills

· Experience with test automation scripting using JavaScript, Python, or similar languages.

· Exposure to CI/CD pipelines and tools such as Jenkins, GitHub Actions, AWS DevOps, or GitLab CI.

· Understanding of cloud-based applications, microservices architecture, and API-driven systems.

· Knowledge of AI-driven test automation platforms and intelligent test execution tools.