About the Role
This position is listed on behalf of a partner company. The partner company is seeking an AI-native QA Engineer to be based in Saudi Arabia. This role is designed for a QA professional who will leverage AI to redefine quality assurance processes and scaling. The position operates within a fast-moving startup environment focused on experimentation, automation, and speed. The core of this role involves building intelligent QA systems powered by Large Language Models (LLMs) to accelerate test creation, execution, and defect analysis. The engineer will contribute to enhancing product reliability across complex AI-driven workflows and agent-based systems. Collaboration with engineering, product, and R&D teams will ensure releases are robust, validated, and production-ready. This is a high-impact role where QA is integrated as a core component of the AI development lifecycle.
In this role, you will design and evolve AI-powered QA systems to improve automation coverage, enhance defect detection, and strengthen release confidence for AI-driven products.
Key Responsibilities
- Build and maintain AI-powered QA frameworks that automate test design, test execution, and validation workflows using LLM-assisted tools and modern automation stacks.
- Develop automated test suites for functional, regression, integration, and performance testing across complex agent-based systems.
- Utilize LLMs (such as GPT, Claude, and similar models) to accelerate test generation, bug analysis, and workflow validation.
- Analyze defects and production incidents, identify root causes, and implement preventive testing strategies to reduce regressions.
- Integrate automated testing pipelines into CI/CD workflows to ensure continuous quality validation.
- Collaborate with engineering and product teams to define test strategies and ensure robust release validation.
- Improve QA processes, expand test coverage, and enhance automation efficiency across evolving systems.
Required Qualifications
- 3+ years of QA experience, with at least 2+ years in test automation roles.
- Proven hands-on experience using LLMs (GPT, Claude, Llama, or similar) in QA workflows and automation pipelines.
- Strong programming skills in Python, with expertise in PyTest and test automation frameworks.
- Solid understanding of REST APIs, client-server architecture, and web service testing.
- Experience working with SQL databases such as PostgreSQL or ClickHouse.
- Familiarity with CI/CD pipelines and automated testing integration.
- Strong analytical thinking and the ability to work independently on complex systems and logic.
- Ability to align work with EST time zone requirements.
Key Skills
- AI-native QA Engineering
- Artificial Intelligence (AI)
- Large Language Models (LLMs)
- Test Automation
- Automation Coverage
- Defect Detection
- Release Confidence
- AI-Powered QA Frameworks
- LLM-Assisted Tools
- Modern Automation Stacks
- Automated Test Suites
- Functional Testing
- Regression Testing
- Integration Testing
- Performance Testing
- Agent-Based Systems
- Test Generation
- Bug Analysis
- Workflow Validation
- Defect Analysis
- Root Cause Analysis
- Preventive Testing Strategies
- CI/CD Pipelines
- Continuous Quality Validation
- Test Strategies
- Release Validation
- QA Processes
- Test Coverage
- Automation Efficiency
- Python Programming
- PyTest
- Test Automation Frameworks
- REST APIs
- Client-Server Architecture
- Web Service Testing
- SQL Databases
- PostgreSQL
- ClickHouse
- Automated Testing Integration
- Analytical Thinking
- Complex Systems and Logic
- AI Tools
Work Environment and Details
This is a full-time position based in Saudi Arabia. The role is part of a fast-paced startup culture that emphasizes strong engineering collaboration. The company offers a competitive compensation package aligned with experience. A remote-first work environment is provided, along with 20 paid time off days plus * holidays. Access to a modern AI-driven technology stack is available, offering a high degree of autonomy and freedom to experiment with new tools and approaches. Support for professional development and learning reimbursement is also provided.
Jobgether utilizes an AI-powered matching process for efficient and objective candidate review. Shortlisted candidates are shared with the hiring company for final decisions. By applying, you acknowledge that Jobgether will process your personal data for evaluation and sharing with the hiring employer, based on legitimate interest and pre-contractual measures. You may exercise your data rights at any time. AI tools may support parts of the hiring process, assisting the recruitment team.