Insurance Policy Operations Lead for AI Training

Mercor; Oslo fylke; In loco; NOK 765.000 - 918.000; Tempo pieno

Descrizione del lavoro

Mercor is partnering with a leading AI lab to train frontier models for insurance reasoning. We seek Policy Administration and Insurance Operations Managers to design policy-processing scenarios, evaluate model outputs against standards, and deliver practical feedback to improve AI behavior.

Applicants should have hands-on policy administration experience and a deep understanding of the policy lifecycle. The role involves onboarding and ongoing calibration sessions to align model outputs with

Competenze

• 2+ years of professional experience in policy administration, underwriting operations, insurance servicing or policy-processing management.
• Strong understanding of the policy lifecycle from intake to record retention.
• Hands-on experience with policy administration systems and workflow controls.
• Ability to translate requirements into precise operational steps and checklists.
• Excellent written communication, process discipline and attention to detail.

Mansioni

• Design realistic scenarios for application intake, binding, issuance, endorsements, billing, renewals and document delivery.
• Create work products such as processing instructions, transaction reviews and quality checks.
• Write reference responses at experienced insurance-operations quality.
• Grade AI-generated responses against rubrics for procedural accuracy and completeness.
• Identify issues like incorrect dates, missing docs, or misaligned underwriting decisions.
• Provide written feedback to improve model behavior.
• Participate in onboarding hours and calibration sessions.

Conoscenze

Policy administration

Insurance operations

Quality assurance

Operational processes

Strumenti

Policy administration systems

Descrizione del lavoro

Mercor is partnering with a leading AI lab to train frontier models for insurance reasoning. We seek Policy Administration and Insurance Operations Managers to design policy-processing scenarios, evaluate model outputs against standards, and deliver practical feedback to improve AI behavior.

Applicants should have hands-on policy administration experience and a deep understanding of the policy lifecycle. The role involves onboarding and ongoing calibration sessions to align model outputs with