Remote Business Development Ops QA Contractor

AI Trainer Jobs

United States

Remote

USD 48,000 - 69,000

Part time

5 days ago
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Job summary

AI Trainer Jobs is seeking a Business Development Contractor to remotely review AI outputs across contractor operations workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk, and document the right next step so the modeling team can train on it.

This contractor role offers flexible async hours and pays $35-50 per hour, depending on program demand and reviewer confirmation, with placement defined by current program needs.

Qualifications

  • Direct working experience in business development contractor specialist operations on real teams for Business Development Contractor work.
  • Comfort applying multi-page rubrics consistently across long batches.
  • Clear written reasoning that names the policy or workflow being applied.
  • Strong attention to detail and the ability to flag when a prompt itself is the problem.
  • Reliable async availability for at least 10 hours per week.

Responsibilities

  • Review AI outputs against current business development contractor specialist operations workflows, playbooks, and firm policy for Business Development Contractor 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.

Skills

Operational review
Policy adherence
Workflow judgment
Stakeholder communication
BD contractor operations

Job description

AI Trainer Jobs is seeking a Business Development Contractor to remotely review AI outputs across contractor operations workflows. Reviewers grade workflow correctness, policy adherence, and stakeholder fit; flag operational risk, and document the right next step so the modeling team can train on it.

This contractor role offers flexible async hours and pays $35-50 per hour, depending on program demand and reviewer confirmation, with placement defined by current program needs.

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