Senior Quality Assurance Engineer

QA Engineer

Location: Remote

Experience: 3 to 6 years

Employment Type: Full-time, Remote

About the client

The client is building the future of scalable, cloud-native solutions. Based in the vibrant tech hub of Abu Dhabi, they operate with a fully remote, global mindset. They believe in high autonomy, clean code, and engineering excellence.

Role Overview

As a QA Engineer, you will play a vital role in ensuring the quality, reliability, and accuracy of our AI-driven platforms and applications. You will be responsible for defining test strategies, executing end-to-end testing, validating complex AI outputs, and conducting load and performance tests. Working closely with our engineering and product teams, you will champion quality across the entire development lifecycle in a fast-paced environment.

Key Responsibilities

AI System & Output Validation: Validate non-deterministic AI/ML model outputs, evaluate model response accuracy, drift, and edge cases, ensuring robust validation frameworks for AI-generated content.

Functional & Regression Testing: Design, write, and execute comprehensive test suites for functional and regression testing to maintain product stability across new releases.

Performance & Load Testing: Plan and execute load, stress, and performance testing to ensure systems remain performant, scalable, and resilient under high concurrency.

Automated & Manual Quality Assurance: Build and maintain automated test scripts for API and UI layers while performing exploratory manual testing when required.

Defect Management & Reporting: Identify, document, track, and prioritize bugs and regressions, collaborating closely with developers to drive swift resolutions.

CI/CD Integration: Integrate automated test suites into CI/CD pipelines to ensure continuous quality and rapid feedback loops.

Qualifications & Skills

• Mandatory AI Testing Experience: Direct experience testing AI/ML models, LLM applications, or AI-driven workflows, including output validation, accuracy assessment, and edge-case handling.
• Core QA Expertise: Mastery in functional, regression, integration, and end-to-end (E2E) testing methodologies.
• Performance & Load Testing: Hands-on experience with load testing tools (e.g., JMeter, Locust, k6, or similar) to evaluate application performance and throughput.
• Test Automation: Proficiency with automation frameworks (e.g., Playwright, Cypress, Selenium, or PyTest) and API testing tools (e.g., Postman, REST Assured).
• Technical & Database Skills: Familiarity with Python, RESTful APIs, and querying databases (SQL/NoSQL) to verify data integrity and validate back-end workflows.
• Cloud & DevOps Mindset: Familiarity with modern cloud environments (AWS/GCP/Azure)and continuous integration pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).