SME CareersFirst seen Civil Engineer Quality Assurance Lead (QAL)
Up to $105/hr
Remote STEM contract with SME Careers, up to $105/hr, open to people in United States. First seen Oct 28.
Up to $105/hr
Apply on SME CareersIs this job worth applying to?
- Pay
- Above typicalTops out at $105/hr. The typical top rate across 148 priced STEM listings is $70/hr.
- Getting in
- Some screening~30 min: profile + 15-min AI interview. Credentials in your field.
- Steady work
- Work is patchyProjects can end a placement for quality issues.
- Payout record
- Pays on timeSchedule: weekly. Paid via Deel.
- Freshness
- No post dateSME Careers doesn't publish post dates. First seen Oct 28, 2026; still listed Nov 6, 2026.
- Where you live
- Named countries onlyOpen in United States.
The job description
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 escalate 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.
How do you apply to SME Careers?
Apply on SME Careers
The Apply button opens this post on SME Careers's own site. You apply with them, not with Rubric. Budget about 30 min: profile + 15-min AI interview.
Get through screening
What SME Careers asks for after you apply:
- Do the ~15-minute English AI video interview on a desktop (up to 3 attempts)
- Take any written or video qualification exam
- Sign the Deel contract and join Discord
- Wait for a project offer by email
Start work and get paid
Pay schedule: weekly. Paid via Deel. You're paid for the work they hand out, not a fixed salary.
SME Careers also needs
- Credentials in your field
- Desktop with webcam
- Deel account
Red flags
None on record for SME Careers. A real platform never asks you to pay for training, equipment or a "starter kit".
What is SME Careers like to work for?
SuperAnnotate's expert-hiring site, which places credentialed specialists on hourly AI training contracts paid through Deel.
| Advertised pay | $20–130/hr |
|---|---|
| Getting in | Some screening |
| Application takes | ~30 min: profile + 15-min AI interview |
| How you get paid | Weekly, via Deel |
| Payout record | Pays on time |
| Countries | Hires in nearly 90 countries, including India, Nigeria, Kenya, Pakistan and the Philippines; sanctioned countries are excluded and some projects set region or language rules. |
Listings show only an 'up to' rate: about $20/hr for generalists, $60/hr software, $90/hr healthcare and $110/hr legal; your actual rate depends on credentials and location.
