Insurance Policy Operations Lead - Policy Admin & QA

Weekday Ai; New Zealand; Sur place; NZD 60 000 - 100 000; Plein temps

Résumé du poste

Weekday Ai in New Zealand seeks Policy Administration and Insurance Operations Managers to design realistic policy-processing scenarios and evaluate AI outputs against established standards. You’ll help shape how AI reasons about the policy lifecycle and servicing workflows are implemented.

We welcome professionals with experience in policy issuance, endorsements, billing, renewals, and servicing activities, and you will work closely with the research team to improve model behavior.

Qualifications

• 2+ years of professional experience in policy administration or underwriting operations.
• Understand lifecycle from intake, issuance, servicing, renewal to termination.
• Hands-on experience with policy administration systems and quality assurance processes.
• Strong written communication and meticulous attention to detail.

Responsabilités

• Design scenarios across policy lifecycle including issuance, endorsements, billing and cancellations.
• Create work products like processing instructions and quality checks.
• Write reference responses at a high level.
• Grade AI outputs against rubrics for accuracy and timeliness.
• Provide feedback to improve model behavior.
• Participate in onboarding hours and calibration sessions.

Connaissances

Policy administration

Quality assurance

Written communication

Process improvement

Outils

Policy administration systems

Workflow queues

Transaction controls

Description du poste

Weekday Ai in New Zealand seeks Policy Administration and Insurance Operations Managers to design realistic policy-processing scenarios and evaluate AI outputs against established standards. You’ll help shape how AI reasons about the policy lifecycle and servicing workflows are implemented.

We welcome professionals with experience in policy issuance, endorsements, billing, renewals, and servicing activities, and you will work closely with the research team to improve model behavior.