Legal Quality Assurance Lead; QAL

Pay: up to $120/hour

In this hourly, remote contractor role, you will work as a Legal Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across legal AI training projects. You will review AI-generated legal 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 legal reasoning quality, issue spotting, jurisdictional awareness, citation and source handling, clarity, risk awareness, formatting, instruction-following, 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 legal expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote legal-review teams.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of Super Annotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your legal quality leadership will directly help improve the world’s premier AI models by ensuring that legal training data is accurate, well-reasoned, clearly explained, appropriately cautious, 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.

• Quality monitoring:
  Spot-check legal items, identify quality issues, provide ongoing feedback through DMs, and
  ** escalate
  * * recurring or critical issues.
• Legal review:
  Evaluate AI-generated legal explanations, legal research responses, contract analyses, policy interpretations, case summaries, compliance guidance, and issue-spotting workflows for accuracy, clarity, and appropriate caution.
• Trainer and QA communication:
  Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and legal-review-specific standards.
• Question handling:
  Respond to trainer/QA questions clearly and promptly, especially around legal reasoning, jurisdiction, citations, source quality, disclaimers, contract language, compliance interpretation, and rubric application.
• 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 legal project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, 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 legal-specific review requirements.
• Quality alignment:
  Ensure all trainers and QAs apply legal-review guidelines consistently and understand updates as projects evolve.
• Risk and safety review:
  Flag unsafe, misleading, overconfident, or jurisdictionally inappropriate legal outputs, especially where the content could be interpreted as personalized legal advice.
• Process improvement:
  Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for legal AI training projects.

• Bachelor’s…