Civil Engineer Quality Assurance Lead (QAL)

SuperAnnotate AI, Inc.; United States; On-site; USD 87,000 - 145,000; Part time

Job summary

SME Careers in the United States is seeking a Civil Engineering Quality Assurance Lead (QAL) for an hourly remote contractor role. You will oversee quality, trainer performance, and adherence to project rubrics across civil engineering AI training projects.

You will review AI-generated content, provide precise feedback, and ensure compliance with safety, units, and standards while coordinating with remote trainers and QAs.

Qualifications

• Bachelor’s or Master’s degree in Civil/Structural/Geotechnical/Transportation/Environmental/Construction engineering or related field.
• Strong English communication to provide clear technical feedback.
• 3+ years of professional civil engineering experience in related workflows.
• Solid knowledge of statics, structural analysis, reinforced concrete, steel design, soil mechanics, foundations.
• Familiarity with AutoCAD, Civil 3D, Revit, and other listed tools preferred.
• Experience leading or supporting remote teams of trainers and reviewers.

Responsibilities

• Quality monitoring of civil engineering items and providing ongoing feedback.
• Technical review of AI-generated engineering explanations and calculations.
• Communicate updates to trainers and QAs via Discord.
• Respond to questions around engineering assumptions, units, formulas, loads, and safety.
• Manage activation of inactive contributors and track follow-ups.
• Create and maintain civil engineering project documentation and style guides.
• Schedule onboarding/training calls detailing expectations and rubrics.
• Ensure consistent application of engineering guidelines across projects.
• Flag unsafe or misleading recommendations impacting safety.
• Identify quality gaps and propose scalable QA processes.

Skills

Documentation

Geotechnical Engineering

Trainer Feedback

Civil Engineering

Transportation Engineering

Technical Review

Engineering QA

AI Training

LLM evaluation

Structural Analysis

Education

Bachelor’s or Master’s degree in Civil Engineering or related field

Tools

AutoCAD

Civil 3D

Revit

ETABS

SAP2000

STAAD.Pro

SAFE

HEC-RAS

HEC-HMS

ArcGIS/QGIS

Bluebeam

Excel

MATLAB

Python

Job description

Pay: up to $105/hour

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.

Responsibilities

• Quality monitoring: Spot-check civil engineering items, identify quality issues, provide ongoing feedback through DMs, and escalation recurring or critical issues.
• Technical review: Evaluate AI-generated engineering explanations, structural calculations, geotechnical reasoning, construction guidance, infrastructure recommendations, diagrams/descriptions, and problem-solving workflows for correctness and clarity.
• Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and civil-engineering-specific review standards.
• Question handling: Respond to trainer/QA questions clearly and promptly, especially around engineering assumptions, units, formulas, loads, factors of safety, design constraints, standards references, and rubric interpretation.
• 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 civil engineering 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 civil-engineering-specific review requirements.
• Quality alignment: Ensure all trainers and QAs apply engineering guidelines consistently and understand updates as projects evolve.
• Risk and safety review: Flag unsafe, misleading, or overconfident engineering recommendations, especially where structures, infrastructure, construction safety, foundations, transportation systems, drainage, or public safety may be affected.
• Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for civil engineering AI training projects.

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.

Skills: Documentation, Geotechnical Engineering, Trainer Feedback, Civil Engineering, Transportation Engineering, Technical Review, Engineering QA, AI Training, LLM evaluation, Structural Analysis

Open to candidates in: The United States

Interview language: English