المسمى الوظيفي

Role overview

This opportunity is for a Saudi Arabia–based AI-native QA Engineer working for a partner company that handles the application process and all next steps. The position is intended for a quality assurance specialist who uses AI as a core part of testing, not just as an add-on. You will operate in a fast-moving startup setting where rapid experimentation, automation, and delivery speed matter. The job centers on building smart QA systems with large language models to speed up test creation, execution, and defect investigation. You will help raise product reliability across complex AI workflows and agent-based systems, and you will work closely with engineering, product, and R&D teams to keep releases validated and production-ready.

Key accountabilities

Create and evolve AI-enabled QA systems that expand automation coverage, improve defect discovery, and increase confidence in releases for AI-driven products.
Develop automated test coverage for functional, regression, integration, and performance scenarios in sophisticated agent-based environments.
Apply LLMs such as GPT, Claude, and similar tools to speed up test generation, defect investigation, and workflow validation.
Investigate failures and production incidents, trace root causes, and introduce preventive testing methods to minimize regressions.
Connect automated testing to CI/CD pipelines so quality checks run continuously throughout delivery.
Partner with engineering and product stakeholders to shape test strategy and validate releases thoroughly.
Strengthen QA processes, broaden coverage, and raise automation efficiency as the platform evolves.

Requirements

At least 3 years of QA experience, including 2 or more years focused on test automation.
Practical, hands-on use of LLMs such as GPT, Claude, Llama, or comparable models within QA workflows and automation pipelines.
Strong Python programming ability, with solid experience using PyTest and related automation frameworks.
Good understanding of REST APIs, client-server systems, and web service testing.
Experience working with SQL databases, including PostgreSQL or ClickHouse.
Familiarity with CI/CD pipelines and how to integrate automated testing into them.
Strong analytical thinking and the ability to work independently on complex logic and systems.
Availability to align with EST working hours.

Benefits

Compensation aligned with experience and market expectations.
Remote-first work setup.
20 paid time off days in addition to U.S. holidays.
Access to a modern AI-focused technology stack.
High autonomy and room to experiment with new tools and methods.
Support for professional development and learning reimbursement.
Startup environment with fast execution and close collaboration across engineering teams.

Application and data handling

The hiring company manages review, interviews, assessments, and final decisions directly. Applications are screened through an AI-assisted matching process that compares candidates against the role requirements before a shortlist is shared with the employer.

By submitting an application, candidates acknowledge that personal data may be processed to assess candidacy and share relevant details with the hiring employer under applicable data protection principles, including legitimate interest and pre-contractual processing where relevant. Applicants may exercise rights such as access, correction, deletion, and objection. AI tools may assist with parts of the recruitment workflow, such as application review, resume analysis, and response assessment, but human judgment remains central to final hiring decisions.

AI-native QA Engineer