Civil Engineer Quality Assurance Lead (QAL)

In this hourly, remote contractor role, you will work as a Civil Engineering Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across civil engineering AI training projects. You will review AI-generated civil engineering 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 technical accuracy, engineering reasoning, calculation correctness, standards awareness, unit consistency, safety considerations, clarity, 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 civil engineering expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical 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 civil engineering quality leadership will directly help improve the world’s premier AI models by ensuring that engineering training data is accurate, logically sound, clearly explained, 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.

Requirements: - Bachelor’s or Master’s degree in Civil Engineering, Structural Engineering, Geotechnical Engineering, Transportation Engineering, Environmental Engineering, Construction Engineering, or a closely related engineering field. - Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear technical feedback in English. - 3+ years of professional experience in civil engineering, structural design, geotechnical engineering, transportation planning, construction management, infrastructure design, water resources, environmental engineering, technical review, engineering education, or related workflows. - Strong understanding of core civil engineering topics such as statics, structural analysis, reinforced concrete, steel design, soil mechanics, foundations, hydraulics, hydrology, transportation systems, surveying, construction materials, and engineering drawing interpretation. - Ability to evaluate engineering content against detailed rubrics and identify issues such as incorrect assumptions, flawed calculations, missing units, unsafe recommendations, code/standards hallucinations, incomplete explanations, or unrealistic design guidance. - Familiarity with common civil engineering tools or workflows such as AutoCAD, Civil 3D, Revit, ETABS, SAP2000, STAAD.Pro, SAFE, HEC-RAS, HEC-HMS, ArcGIS/QGIS, Bluebeam, Excel, MATLAB, or Python is preferred. - Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, 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, calibration tasks, and other quality documentation. - Experience with AI training, data annotation, large language models, prompt/response evaluation, technical content QA, or rubric-based LLM evaluation is a strong plus.