Arabic Team Lead

In this hourly, remote contractor role, you will work as an Arabic Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Arabic AI training projects. You will review AI-generated Arabic content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for accuracy, fluency, grammar, spelling, tone, cultural appropriateness, meaning preservation, instruction-following, formatting, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong Arabic and English skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote teams. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Arabic quality leadership will directly help improve the world’s premier AI models by ensuring that Arabic training data is natural, accurate, culturally appropriate, well-documented, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Responsibilities

• Quality monitoring: Spot-check Arabic items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, and quality expectations.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around Arabic wording, grammar, register, dialect, RTL formatting, translation fidelity, terminology, and cultural context.
• Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Documentation: Create and maintain Arabic project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, and onboarding materials.
• Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and Arabic-specific style requirements.
• Quality alignment: Ensure all trainers and QAs apply Arabic language guidelines consistently and understand updates as projects evolve.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for Arabic-language projects.

Requirements

• 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 to follow project guidelines, communicate with teams, and provide clear feedback in English.
• 3+ years of professional experience in Arabic writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows.
• 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.