[![Image]() Meet Jobicy Copilot — free AI autofill for job applications + remote job alerts ›](#) [All remote jobs](https://jobicy.com/jobs.md)Open role[![Brain Co. logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/08/b2bdd014-221.png)](https://jobicy.com/company/brain-co.md)Remote opportunity at[Brain Co.](https://jobicy.com/company/brain-co.md) # Specialty Insurance Underwriter/Coverage Attorney/Consultant/Professional (Contract) Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/brain-co.md)Share5 Sep 2026Published58Listing views3Application actions5 Oct 2026Apply before Opportunity details ## About this role. AI SummaryBrain Co. seeks a USA-based specialty insurance expert to serve as a part-time contract subject-matter consultant for an AI product. The consultant will annotate policies, assess AI-generated coverage analyses, and establish expert rubrics for extraction and reasoning quality. Core work centers on excess and specialty insurance policies, including limits, retentions, attachment points, endorsements, exclusions, and layered programs. Candidates need at least three years of relevant experience, with five or more years strongly preferred, and must translate insurance practice clearly for engineers and product teams. The initial commitment is approximately 2–10 hours weekly for three to four months, with possible extension. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 4/5EasyHard ### Pace & Pressure 3/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 5/5IndependentCollaborative AI insightThis role requires nuanced, practitioner-level interpretation of specialty and excess policy language, including ambiguous manuscript wording and complex coverage structures. The expert must independently form defensible conclusions while converting them into repeatable standards for a non-insurance technical team. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianMarket rate$125US market range$90–$1750$193 AI insightNo numeric compensation is disclosed; the posting only states that the hourly rate is competitive and commensurate with experience. Estimated US contract-market compensation for an experienced specialty insurance underwriter, coverage attorney, or consultant performing part-time AI policy-review work is approximately $90–$175 per hour, with an estimated median of $125 per hour. Actual rates may vary materially based on attorney licensure, claims expertise, specialty line depth, and consulting seniority. ## Core skills Skills and capabilities most closely associated with this opportunity. [Specialty Insurance](https://jobicy.com/jobs?search_keywords=Specialty%20Insurance.md)[Excess and Surplus Lines](https://jobicy.com/jobs?search_keywords=Excess%20and%20Surplus%20Lines.md)[Coverage Analysis](https://jobicy.com/jobs?search_keywords=Coverage%20Analysis.md)[Insurance Underwriting](https://jobicy.com/jobs?search_keywords=Insurance%20Underwriting.md)[Policy Interpretation](https://jobicy.com/jobs?search_keywords=Policy%20Interpretation.md)[Claims Analysis](https://jobicy.com/jobs?search_keywords=Claims%20Analysis.md)[Coverage Counsel](https://jobicy.com/jobs?search_keywords=Coverage%20Counsel.md)[Policy Annotation](https://jobicy.com/jobs?search_keywords=Policy%20Annotation.md)[AI Quality Assurance](https://jobicy.com/jobs?search_keywords=AI%20Quality%20Assurance.md) Sample interview questionsHow would you analyze the limits structure of a follow-form excess policy?I would first identify the excess policy’s stated limit, attachment point, schedule of underlying insurance, and any follow-form or limiting language. I would then compare the underlying policy terms, endorsements, exhaustion requirements, and aggregate provisions to determine how the layer attaches and whether any coverage gaps or narrower excess terms apply. Describe how you would assess whether an AI-generated coverage conclusion is correct. I would trace the output back to the specific insuring agreement, definitions, exclusions, conditions, endorsements, and factual assumptions it relies on. I would verify both the substantive conclusion and whether the AI accurately represented uncertainty, conflicts in wording, and the effect of relevant policy layers. What makes manuscript policy wording particularly challenging to review? Manuscript wording often departs from standard forms, may contain internally inconsistent language, and can change the effect of familiar exclusions or conditions. I would evaluate the actual wording in context rather than rely on assumed market conventions, then document the interpretive rationale and any unresolved ambiguity. How would you communicate a complex coverage issue to engineers who do not have insurance experience? I would begin with a plain-language description of the business issue, identify the exact policy language that controls, and explain the decision path step by step. I would use structured examples, define specialized terms, and distinguish firm rules from judgment calls or market-practice assumptions. How would you build a rubric for evaluating AI extraction of insurance policy data? I would define the required fields, permissible values, source-text references, and treatment of ambiguity for each extraction target. The rubric would separately score factual accuracy, completeness, correct association of terms to the applicable coverage layer, and whether the system appropriately flags uncertain or conflicting language. ### Our Mission Rebuild how the world works, to make institutions work better for the people they serve. ### About Brain Co. Brain Co. builds AI-native operating systems for large, regulated institutions. Each system is built for a specific industry, powered by agents that push real workflows forward. Underneath it all is Atlas, our proprietary platform that keeps customers in control, secure by design, and never locked into one model. ### Why Now Brain Co. is entering its next phase of production deployments on a national scale with an elite team built from Palantir, Google, Meta, and Nvidia, and a growing footprint across government, insurance, health, and financial services. Joining now means shaping both the company and a new category of applied AI. Every project here ships to production and is expected to create measurable customer value and impact. You’ll work alongside exceptional peers on some of the hardest problems in applied AI. It’s the kind of work you’ll still be proud of in ten years from now. 𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗥𝗼𝗹𝗲 Brain Co is applying frontier AI to specialty insurance. We are building AI that reads specialty insurance policies — declarations, forms, endorsements, schedules of underlying, layered programs — and turns them into structured, decision-ready data. We need experienced specialty insurance underwriters/coverage attorneys/consultants/professionals to help us do it right. You will work directly with our engineering team: telling us where our AI falls short, annotating insurance documents, reviewing AI-generated output, and helping us build the rubrics and benchmarks that define quality for our machine learning pipelines. Your expertise shapes the product so it reflects how specialty insurance is actually practiced. We are looking for someone who can commit approximately 2–10 hours per week for an initial 3–4 months, with the opportunity to extend based on mutual interest and project needs. 𝗪𝗵𝗮𝘁 𝗬𝗼𝘂 𝗪𝗶𝗹𝗹 𝗗𝗼 • 𝗔𝗻𝗻𝗼𝘁𝗮𝘁𝗲 𝗽𝗼𝗹𝗶𝗰𝘆 𝘁𝗼𝘄𝗲𝗿𝘀. Locate and annotate the limits structure within a given excess policy — limits, sublimits, retentions, attachment points, and how the layers stack. • 𝗥𝗲𝗻𝗱𝗲𝗿 𝗰𝗼𝘃𝗲𝗿𝗮𝗴𝗲 𝗰𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻𝘀. Given an insuring agreement and its ensuing exclusions, produce a structured conclusion about how coverage responds to a described scenario. • 𝗤𝗔 𝗮𝗻𝗱 𝗰𝗼𝗿𝗿𝗲𝗰𝘁 𝗹𝗮𝗯𝗲𝗹𝗶𝗻𝗴. Review AI-generated output, fix mislabeled data, and grade agent performance against what a seasoned practitioner would conclude. • 𝗔𝗱𝗷𝘂𝗱𝗶𝗰𝗮𝘁𝗲 𝘁𝗵𝗲 𝗵𝗮𝗿𝗱 𝗰𝗮𝘀𝗲𝘀. Resolve the ambiguous, conflicting, and unusual situations — manuscript wordings, follow-form excess, nested exclusions, schedule-of-underlying disputes, implicit market conventions — that determine whether a product is trusted by real practitioners. • 𝗕𝘂𝗶𝗹𝗱 𝗲𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 𝗿𝘂𝗯𝗿𝗶𝗰𝘀. Partner with our team to design the scoring criteria and review workflows that tell us, line by line, whether an extraction or a coverage conclusion is accurate. • 𝗦𝗵𝗮𝗽𝗲 𝗽𝗿𝗼𝗱𝘂𝗰𝘁 𝗯𝗲𝗵𝗮𝘃𝗶𝗼𝗿. Help us decide how coverage should be interpreted and presented — what a practitioner needs to see, in what structure, and what would mislead them. Translate practice into product requirements. • 𝗕𝗲 𝗼𝘂𝗿 𝘁𝗿𝗮𝗻𝘀𝗹𝗮𝘁𝗼𝗿. Sit between the documents and the engineers: explain terminology, market convention, and the “why” behind how things are done, and flag where our assumptions do not match reality across lines of business. • 𝗗𝗲𝗳𝗶𝗻𝗲 𝗴𝗿𝗼𝘂𝗻𝗱 𝘁𝗿𝘂𝘁𝗵. Review real policies, endorsements, and claims documents and tell us the correct answer — coverages, limits, sublimits, retentions, attachment points, exclusion logic, and how layers stack — so we can measure and improve the AI against an expert standard. 𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗱 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 • USA-based. 3 years of experience minimum; 5+ years strongly preferred, specifically within excess and specialty insurance. • Experience in excess and specialty (E&S) insurance as an underwriter, coverage attorney or counsel, or consultant. 𝗪𝗵𝗼 𝘄𝗲’𝗿𝗲 𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗳𝗼𝗿 • Have deep, hands-on experience in specialty insurance – underwriting, claims, broking, or coverage counsel — and/or broad multiline experience across the lines we work in (General Liability, Professional Liability, and related casualty and specialty lines). • Can read a policy end-to-end — declarations, forms, endorsements, schedules of underlying — and explain precisely how coverage responds, including across primary and excess layers. • Have strong opinions on what “correct” means and can articulate the reasoning, not just the verdict, so it can be encoded into an AI system. • Communicate clearly with non-insurance experts and enjoy the back-and-forth of teaching engineers your craft. • No technical background required – your job is to tell us if the AI gets it right, not to explain how it works 𝗡𝗶𝗰𝗲 𝘁𝗼 𝗛𝗮𝘃𝗲 • Claims experience — working as, or closely alongside, claim adjusters, claim examiners, complex or litigated claims specialists, or claims counsel. 𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻 & 𝗟𝗼𝗴𝗶𝘀𝘁𝗶𝗰𝘀 • Part-time, contract engagement with flexible scheduling that fits your current work. • Competitive hourly rate commensurate with experience and depth of expertise. • Remote-friendly, with collaboration over shared documents and working sessions with our AI and product teams. Show more [Apply now >](https://jobicy.com/jobs/152609-specialty-insurance-underwriter-coverage-attorney-consultant-professional-contract.md) > Annual salary information is not provided for this position. 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