QA Engineer

Job Overview

The QA Engineer owns testplanning, test case design, execution, and defect management to ensure delivered solutions meet functional, quality, and business requirements. This role covers both manual and automation testing, applying BDD and other testing methodologies as appropriate to the project.

This role also uses AI tools as a core part of the QA workflow — generating test cases from requirements, building and debugging automation scripts, and producing test documentation faster and more consistently.

The QA Engineer works closely with the Solution Architecture team and local development and project teams throughout the SDLC, and may be required to be based at the customer's office during working hours, with occasional after-office-hours work as needed.

Core Responsibilities

TestPlanning & Strategy

• Develop test plans and test strategies aligned to project scope, requirements, and risk areas
• Define test coverage across functional, regression, integration, and user acceptance testing
• Identify test data, environment, and tooling needs ahead of each testing cycle

TestCase Design & Documentation

• Write clear, traceable test cases from requirements, user stories, and acceptance criteria
• Maintain a well-organized, version-controlled test case repository, mapped back to requirements
• Review requirements and designs early to identify testability gaps and ambiguities

TestExecution & Defect Management

• Execute manual test cases across functional, regression, and UAT cycles, applying BDD (Given-When-Then) and other testing methodologies as appropriate
• Log, prioritize, and track defects to closure, verifying fixes before sign-off
• Produce clear test result reports and documentation for project and client sign-off

TestAutomation

• Build and maintain automation scripts (e.g., Selenium, Playwright, Cypress, Appium) for regression and repetitive test coverage
• Integrate automated tests into CI/CD pipelines in partnership with development and DevOps
• Maintain and refactor automation suites as the application evolves

AI-AssistedQA (Priority Focus — AI Skill Set)

• Use AI tools to generate draft test cases directly from requirements, user stories, or acceptance criteria, then review and refine for accuracy and coverage
• Use AI-assisted "vibe coding" tools (e.g., Claude Code, Cursor, Copilot) to build, debug, and maintain automation scripts faster.
• Use AI to draft and standardize QA documentation — test plans, test summary reports, defect write-ups, and release notes — reviewing outputs for accuracy before sign-off
• Use AI to help identify test coverage gaps and suggest edge cases that manual review might miss
• Build working understanding of AI/LLM concepts (RAG, agentic workflows, MCP) sufficient to design and execute test cases for AI-enabled features, including evaluating AI output quality and consistency

API& Integration Testing

• Test APIs and system integrations using tools such as Postman, REST Assured, or SoapUI
• Validate data flows and integration behavior against technical specifications

UAT Support & Collaboration

• Coordinate and support User Acceptance Testing sessions with clients and business stakeholders
• Work closely with developers to clarify requirements, reproduce issues, and validate fixes
• Partner with Solution Architects and Business Analysts on acceptance criteria and technical feasibility of test scenarios.

Required Qualifications

Education & Experience

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
• 3–5+ years of experience as a QA Engineer, Test Engineer, or in a similar quality assurance role
• Demonstrated experience writing test plans, test cases, and defect reports
• Strong manual testing skills, including experience applying BDD and other test design methodologies
• Experience with at least one test automation framework (Selenium, Playwright, Cypress, or Appium)
• Experience working within Agile/Scrum delivery teams
• Hands-on experience or strong aptitude using AI tools to assist with test case generation, automation scripting, or documentation is highly advantageous.

Technical and Management knowledge

AI-AssistedQA Tools & Techniques

• AI test case generation from requirements/user stories, and AI-assisted test coverage analysis
• AI coding assistants (Claude Code, Cursor, GitHub Copilot) for building and debugging automation scripts
• AI-assisted documentation drafting for test plans, summary reports, and release notes
• Basic understanding of LLM/RAG/agentic AI concepts sufficient to design test cases and evaluation criteria for AI-enabled features.

TestAutomation Frameworks

• Selenium, Playwright, Cypress, or Appium (web and/or mobile)
• TestNG, JUnit, or equivalent test runners and reporting frameworks

APITesting Tools

• Postman, REST Assured, or SoapUI

TestManagement & Documentation Tools

• Jira/Xray, TestRail, Zephyr, or equivalent test case and defect management tools
• Confluence or equivalent for test documentation

CI/CD & Environment Awareness

• Integrating automated tests into CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins)
• Basic awareness of AWS, Azure, and GCP sufficient to test cloud-hosted applications

DefectTracking & Reporting

• Defect lifecycle management using Jira, Bugzilla, or equivalent
• Clear, structured test result reporting for project and client stakeholders.

Working Arrangement

• Working closely with the Solution Architecture team and local project/development teams
• Willing to be based at the customer's office during working hours, with the ability to perform after-office-hours work when required
• Embed within project teams across the SDLC, from requirements review through UAT and release sign-off
• Support client-facing UAT sessions and test result documentation as needed
• Continuously adopt AI-assisted tools to improve testing speed, coverage, and documentation quality