Arabic Quality Assurance Lead (QAL)📣 Job Ad

About the Role: Arabic Quality Assurance Lead

SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, is seeking an Arabic Quality Assurance Lead (QAL). This is an hourly, remote contractor role, project-based, and associated with the region of Mecca, Makkah, Saudi Arabia. The QAL will oversee quality, consistency, and trainer performance across various Arabic AI training projects. Please note: While there is no immediate project for this role, qualified candidates will be among the first experts contacted when relevant opportunities arise, providing access to future projects within our expert network.

Role Purpose and Contribution

The primary purpose of this role is to ensure high-quality Arabic training data for premier AI models. The QAL will review AI-generated Arabic content and the work of trainers and QAs, evaluating output against project guidelines. This involves providing precise written feedback and ensuring all contributors adhere to expected quality standards. Assessments cover accuracy, fluency, grammar, spelling, tone, cultural appropriateness, meaning preservation, instruction-following, formatting, and adherence to project-specific rubrics. The role also involves identifying recurring quality issues, communicating updates to teams, supporting onboarding, maintaining documentation, and assisting in the activation of inconsistent contributors.

Key Responsibilities

• Conduct quality monitoring by spot-checking Arabic items, identifying quality issues, providing ongoing feedback, and escalating critical concerns.
• Communicate updates to trainers and QAs regarding new item guidelines, project changes, workflow updates, and quality expectations.
• Respond to trainer/QA questions clearly and promptly, particularly concerning Arabic wording, grammar, register, dialect, RTL formatting, translation fidelity, terminology, and cultural context.
• Manage trainer/QA activation by engaging inactive contributors, encouraging participation, tracking follow-ups, and flagging availability issues.
• Create and maintain Arabic project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, and onboarding materials.
• Schedule and conduct onboarding/training calls for trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and Arabic-specific style requirements.
• Ensure consistent application of Arabic language guidelines and understanding of project updates by all trainers and QAs.
• Identify recurring quality gaps, propose workflow improvements, and contribute to building scalable QA processes for Arabic-language projects.

Required Qualifications and Experience

• Bachelor’s or Master’s degree in Arabic, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field.
• Native or near-native Arabic proficiency with strong reading and writing skills.
• Strong grasp of the English language for following project guidelines, team communication, and providing clear feedback.
• 3+ years of professional experience in Arabic writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows.

Essential Skills and Competencies

• Strong understanding of Arabic grammar, spelling conventions, punctuation, diacritics, RTL formatting, tone, register, Modern Standard Arabic, and regional Arabic variation.
• Ability to evaluate Arabic content against detailed rubrics and identify issues such as mistranslation, literal phrasing, unnatural tone, incorrect register, dialect inconsistency, hallucinated claims, ambiguity, or inconsistent terminology.
• Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and other quality documentation.
• Experience with AI training, data annotation, large language models, prompt/response evaluation, or rubric-based LLM QA is a strong plus.

Application Process

The selection process for this role involves an AI interview, followed by a domain-specific task, and concludes with an interview with a recruiter.