About the role:We are looking for a QA Engineer with strong knowledge of manual testing across iOS, Android, and Web platforms, combined with strong expertise in backend API testing. A key part of this role is working hand-in-hand with AI testing assistants — using them daily to speed up test design, defect reporting, log analysis, and requirements research. You will help shape and continuously adapt our AI-assisted QA workflows as processes and product requirements change quickly. We offer a service agreement with the full time engagement for a professional based in UAE. 

Responsibilities:- Plan, design, and execute manual test cases for iOS, Android, and Web applications.- Perform functional, regression, exploratory, and cross-platform testing.- Conduct thorough backend API testing (REST, GraphQL), including validation of data flows, business logic, and error handling.- Use AI assistants day-to-day to accelerate QA work: generating and refining checklists/test cases, drafting defect reports, analyzing logs, and researching requirements against implementation.- Set up, tune, and maintain AI working rules, prompts, and skills (project conventions, defect templates, reusable checklists) so the AI produces consistent, high-quality output.- Continuously adapt QA processes and AI workflows to fast-changing requirements, keeping documentation as the single source of truth for both people and AI.- Collaborate with developers, designers, and PMs to clarify requirements and identify potential risks.- Report and track defects with clear reproduction steps, logs, and screenshots.- Maintain test documentation (checklists, test cases, test plans) in Notion.- Participate in release verification, smoke tests, and regression cycles.

Requirements:- 5+ years of experience in manual testing for iOS, Android, and Web applications.- Strong hands-on experience in backend API testing (REST, GraphQL or similar).- Solid understanding of client-server architecture and debugging tools.- Hands-on experience (or strong motivation and aptitude) using AI assistants for QA tasks, and willingness to iterate on prompts/rules to get reliable results.- Ability to work effectively in a fast-changing environment with evolving processes and requirements.- Familiarity with Git-based workflows and CI/CD concepts.- Strong analytical skills, attention to detail, and problem-solving mindset.- Upper-intermediate English for daily communication.

• Nice to have:- Experience configuring AI tooling/workflows (custom rules, prompts, skills, or MCP integrations) for a team.- Experience with log/observability tools (Kibana/Elasticsearch or similar) for debugging failing API calls.- Experience with analytical tools and libraries such as Pandas.- Knowledge of Allure TestOps or other test management/reporting tools.- Understanding of Kubernetes, Docker, or test environment setup.- Basic exposure to UI/API automation (not a core focus of this role).