Remote MEP Data Centers QA & Policy Reviewer

AuraOne; United States; On-site; USD 138,000 - 193,000; Full time

Benefits offered by this job

Remote work eligibility

Contractor-friendly engagement

Job summary

AuraOne is seeking a Mechanical, Electrical & Plumbing (MEP) Expert - Data Centers for a remote review track that evaluates AI outputs against actual MEP workflows, data centers playbooks, and firm policy. This role focuses on real-world operations and helps ensure quality checks align with engineering practice.

You will review AI responses, grade workflow correctness, tone, and escalation logic on a structured rubric, and flag operational risk or policy-adherence gaps with severity tags to

Qualifications

• Direct working experience in Mechanical, Electrical & Plumbing (MEP) Data Centers operations on real teams.
• Clear written reasoning that names the policy or workflow being applied.
• Comfort applying multi-page rubrics consistently across long batches.

Responsibilities

• Review AI outputs against current MEP data centers workflows, playbooks, and firm policy for MEP Expert - Data Centers assignments.
• Grade tone, escalation logic, and stakeholder fit on a structured rubric.
• Flag operational risk, missed escalations, and policy-adherence gaps with severity tags.
• Capture the right next step so the modeling team can train on it.
• Adjudicate disputed treatments against published playbooks or firm guidance.
• Maintain reviewer-quality scores in inter-rater calibration cycles.

Skills

Operational review

Policy adherence

Workflow judgment

Stakeholder communication

MEP Data Centers

Job description

AuraOne is seeking a Mechanical, Electrical & Plumbing (MEP) Expert - Data Centers for a remote review track that evaluates AI outputs against actual MEP workflows, data centers playbooks, and firm policy. This role focuses on real-world operations and helps ensure quality checks align with engineering practice.

You will review AI responses, grade workflow correctness, tone, and escalation logic on a structured rubric, and flag operational risk or policy-adherence gaps with severity tags to