Insurance Expert
Up to $70/hr as listed
- Listed pay
- Up to $70/hr as listed
- Field
- Writing
- Languages
- English
- Where
17 countries
United States, Germany, Brazil, India, Bangladesh, Bhutan, Indonesia, Cambodia, Sri Lanka, Malaysia, Nepal, Philippines, Pakistan, Singapore, Thailand, Timor Leste, Vietnam- Type
- Contract, remote
- Posted on SME Careers
- First seen here
- 9 October 2026
Summary
In this hourly, remote contractor role, you will work as an Insurance Subject Matter Expert (SME) to review AI-generated insurance responses and/or create expert insurance content, evaluating...
From the SME Careers listing
In this hourly, remote contractor role, you will work as an Insurance Subject Matter Expert (SME) to review AI-generated insurance responses and/or create expert insurance content, evaluating reasoning quality and step-by-step decision-making while providing precise written feedback. 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.
Important:
There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.
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.
Requirements
- 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.
Text above is the platform's own listing, shown as published. Check the details on SME Careers before applying.
Prepare for the assessment
Practice questions and what each platform says about its screening for this kind of role:
Terms in this listing
- Prompt
- The input given to a model: a question, an instruction or a conversation so far.
- Assessment
- Any screening step a platform uses before giving you work: a quiz, a skills test, a language test, a writing sample or an AI interview.
- Edge case
- An unusual item the guidelines do not clearly cover. Projects usually ask you to flag it rather than guess.
- Annotation
- Adding labels or notes to data such as text, images, audio or video so a model can learn from it.
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