Civil Engineering Quality Assurance Lead (QAL)

About the Role

This is a remote, hourly contractor role for a Civil Engineering Quality Assurance Lead (QAL) responsible for overseeing quality, consistency, and contributor performance across civil engineering AI training projects.

You will review AI-generated civil engineering content, evaluate trainer and QA work, maintain technical quality standards, support onboarding activities, manage contributor performance, and ensure adherence to engineering review guidelines and evaluation rubrics.

The role combines civil engineering expertise, technical quality assurance, AI evaluation, safety review, contributor support, and process improvement.

Key Responsibilities

Quality Monitoring

• Review civil engineering training items and QA outputs
• Identify quality issues and recurring technical errors
• Provide detailed feedback to contributors
• Escalate critical quality concerns

Technical Review

Evaluate AI-generated structural calculations, geotechnical analyses, construction guidance, infrastructure recommendations, transportation engineering solutions, hydrology and hydraulics reasoning, and technical reasoning workflows.

Verify technical accuracy, engineering logic, calculation correctness, unit consistency, design assumptions, standards awareness, safety compliance, and clarity of explanation.

Trainer & QA Communication

• Communicate guideline updates and workflow changes
• Clarify civil-engineering-specific review standards
• Maintain contributor alignment

Question Resolution

Respond to contributor questions regarding engineering assumptions, structural loads, factors of safety, design constraints, calculations and formulas, unit conversions, foundation design concepts, hydraulics and hydrology, and rubric interpretation.

Contributor Activation Management

• Follow up with inactive contributors and track engagement
• Encourage participation and task completion

Documentation Management

Create and maintain style guides, engineering FAQs, quality notes, calibration tasks, examples, trackers, honeypots, and onboarding materials.

Onboarding & Training

• Conduct onboarding and training sessions
• Explain project workflows, evaluation rubrics, engineering quality standards, technical review procedures, and safety requirements

Risk & Safety Review

Identify and flag unsafe engineering recommendations, dangerous construction guidance, structural safety concerns, foundation-related risks, infrastructure design risks, transportation safety issues, drainage and flood-risk concerns, and public safety hazards.

Process Improvement

• Identify recurring quality gaps and recommend workflow improvements
• Help build scalable QA processes for civil engineering projects

Required Skills & Qualifications

• Bachelor's or Master's degree in Civil Engineering, Structural Engineering, Geotechnical Engineering, Transportation Engineering, Environmental Engineering, or related discipline
• 3+ years of professional experience in civil engineering, structural design, geotechnical engineering, transportation planning, infrastructure design, construction management, or water resources engineering
• Strong understanding of statics, structural analysis, reinforced concrete design, steel design, soil mechanics, foundations, hydraulics, hydrology, transportation systems, surveying, and construction materials
• Ability to identify incorrect assumptions, calculation errors, missing units, unsafe recommendations, code and standards hallucinations, unrealistic design guidance, and engineering design flaws
• Strong written English, technical feedback, and documentation skills

Preferred Qualifications

• Experience with AutoCAD, Civil 3D, Revit, ETABS, SAP2000, STAAD.Pro, SAFE, HEC-RAS, HEC-HMS, ArcGIS, QGIS, MATLAB, or Python
• Experience leading or supporting engineers, technical reviewers, QA teams, or annotation teams
• Experience with AI training, data annotation, LLM evaluation, or rubric-based QA
• Familiarity with Discord, Google Docs, Google Sheets, and project management systems

Additional Information

• Fully remote — Flexible schedule — Weekly payments
• Access to future opportunities through the SME Careers expert network

About SME Careers

SME Careers is an AI data services company and subsidiary of SuperAnnotate that provides training data for leading AI companies and foundation-model laboratories.