Senior QA Engineer (Manual Testing + AI-Assisted QA)

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).