Insurance Expert

About this role

You will assess solutions for accuracy, clarity, regulatory/compliance awareness, and adherence to the prompt; identify errors in policy interpretation, coverage analysis, claims handling logic, underwriting reasoning, risk assessment, exclusions/endorsements, and terminology; fact-check technical insurance information; write high-quality explanations and model solutions that demonstrate correct methods; and rate and compare multiple responses based on correctness and reasoning quality. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs.

Insurance Coverage, Policy Interpretation, Claims Handling, Underwriting, Risk Assessment

Responsibilities

• Develop AI Training Content: Create detailed prompts and gold-standard outputs across coverage analysis, claims scenarios, underwriting decisions, and policy communication.
• Optimize AI Performance: Evaluate and rank AI responses to improve correctness, completeness, clarity, and compliance-aware reasoning.
• Ensure Model Integrity: Test AI outputs for inaccuracies, misleading guidance, inappropriate certainty, and bias; validate reliability across use cases.

Qualifications

• Bachelor’s degree (or higher) in Business, Finance, Risk Management, Insurance, Law, or a related field (or equivalent professional experience).
• 5+ years of professional experience in insurance (claims, underwriting, brokerage, actuarial support, risk management, compliance, or operations).
• Strong understanding of insurance fundamentals: policy structure (insuring agreement, definitions, conditions, exclusions), endorsements, limits/deductibles, and coverage triggers.
• Comfortable with coverage and claims reasoning across one or more lines (e.g., P&C, commercial lines, auto, homeowners, liability, health, life).
• Ability to evaluate decisions for internal consistency (facts → policy language → coverage position → documentation), including edge cases and ambiguity.
• Strong attention to detail when identifying missing facts, incorrect assumptions, misapplied definitions, or unsafe/unsupported recommendations; minimum C1 English proficiency.
• Clear written communication skills, including the ability to explain complex policy concepts in plain language.
• Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.
• Professional designations (e.g., CPCU, AINS, ARM, CIC, AU) are a plus.
• Prior experience with AI data training/annotation, claims QA, underwriting QA, policy drafting/review, or insurance editorial work is strongly preferred.