Remote AI Workflow Auditor – Manufacturing Ops

AuraOne, Inc.; United States; Remote; USD 34,000 - 55,000; Part time

Benefits offered by this job

Flexible schedule

Remote work

Job summary

AuraOne, Inc. seeks a Manufacturing Process Demonstrator reviewer to evaluate AI outputs within real-world manufacturing workflows. You will assess workflow accuracy, policy adherence, and escalation tone while documenting actionable next steps for training the modeling team.

This remote, contract-based role requires reliable weekly availability and the ability to review multi-page rubrics consistently, ensuring high-quality assessments across diverse manufacturing scenarios.

Qualifications

• Direct working experience in manufacturing process demonstrator operations on real teams.
• Clear written reasoning naming policy/workflow applied.
• Strong attention to detail and ability to flag prompt issues.

Responsibilities

• Review AI outputs against current workflows, playbooks, and firm policy.
• Grade tone, escalation logic, and stakeholder fit on a rubric.
• Flag operational risk, missed escalations, and policy gaps with severity tags.
• Capture next steps for model training by the modeling team.
• Adjudicate disputed playbook calls using firm guidance.
• Maintain reviewer quality scores in calibration cycles.

Skills

MPD operations

Policy adherence

Workflow judgment

Stakeholder communication

Robotics & AI

Rubric writing

Expert review

Operational review

AI evaluation

Manufacturing ops

Education

Bachelor's or higher in a relevant field

Tools

AI tooling

Workflow tooling

Job description

AuraOne, Inc. seeks a Manufacturing Process Demonstrator reviewer to evaluate AI outputs within real-world manufacturing workflows. You will assess workflow accuracy, policy adherence, and escalation tone while documenting actionable next steps for training the modeling team.

This remote, contract-based role requires reliable weekly availability and the ability to review multi-page rubrics consistently, ensuring high-quality assessments across diverse manufacturing scenarios.