Architectural Visualization QA Specialist (Remote)

AuraOne Human Data; United States; Remote; USD 96,000 - 165,000; Full time

Benefits offered by this job

Remote contractor

US-eligible

Contractor-friendly engagement

Job summary

AuraOne, Inc. is seeking an Architectural & Interior Visualization AI Evaluation Specialist to remotely review outputs and grade them against workflows and policies.

This role focuses on accuracy, policy adherence, and stakeholder fit, providing clear next steps for model training. As a contractor, you will work asynchronously for at least 10 hours per week, reviewing multi-page rubrics and flagging escalations with precise severity tags to support continuous improvement of AI-assisted

Qualifications

• Experience reviewing architectural interior visualization operations and workflows.
• Ability to apply policy and playbooks consistently across batches.
• Clear written reasoning naming the policy or workflow applied.
• Attention to detail with ability to flag prompt issues.

Responsibilities

• Review AI outputs against workflows, playbooks, and firm policy for AI Evaluation tasks.
• Grade tone, escalation logic, and stakeholder fit on a structured rubric.
• Flag operational risk and policy-adherence gaps with severity tags.
• Capture the right next steps for model training.
• Adjudicate disputed plays using firm guidance.
• Maintain reviewer-quality scores during calibration cycles.

Skills

Operational review

Policy adherence

Workflow judgment

Stakeholder communication

Architectural Interior Visualization

Job description

AuraOne, Inc. is seeking an Architectural & Interior Visualization AI Evaluation Specialist to remotely review outputs and grade them against workflows and policies.

This role focuses on accuracy, policy adherence, and stakeholder fit, providing clear next steps for model training. As a contractor, you will work asynchronously for at least 10 hours per week, reviewing multi-page rubrics and flagging escalations with precise severity tags to support continuous improvement of AI-assisted