Audit AI Outputs: Review AI-generated medical chronologies, gap signals, and summaries to ensure they match real-world clinical and legal reasoning.

Identify Edge Cases: Spot instances where AI outputs are technically coherent but clinically flawed, or where an automated "finding" would be dismissed as noise by an attorney.

Annotate Datasets: Review, tag, and annotate real medical records to create gold-standard "ground truth" datasets for pipeline testing.

Define Pass/Fail Rubrics: Partner with engineering to establish strict, defensible criteria and grading scales for model performance (evals).

Stress-Test Features: Actively "red-team" new model iterations to catch potential errors, hallucinations, and documentation oversights before they ship.

Advise Product & Engineering: Serve as an on-demand domain consultant for Product Managers and Engineers to shorten technical iteration loops.

Map Billing Nuances: Translate the complexities of Explanation of Benefits (EOBs) versus itemized bills and provider-level gap detection into logical rules for developers.

Shape the Feature Roadmap: Provide expert guidance on upcoming high-stakes features, including Missing Documents V2, Treatment Gaps, and automated demand letter artifacts.

Refine Topic Taxonomies: Establish the clinical classification rubrics for our "Smart Summaries" feature, ensuring data is organized exactly how practitioners think.

Domain Expertise: 3 to 5+ years of direct, hands-on experience in personal injury case preparation, medical-legal consulting, or clinical documentation review.

Professional Background: Background as a Personal Injury Paralegal, Legal Assistant, Nurse Case Manager, Life Care Planner, or Health Information/Billing Specialist.

Record Mastery: Deep, expert-level familiarity with reviewing medical records, summarizing treatments, and navigating provider documentation standards.

Billing Literacy: Strong understanding of medical billing practices, including itemized statements, EOBs, insurance billing, and CPT codes.

Meticulous Precision: An exceptional eye for detail, with the proven ability to spot missing treatment gaps or subtle clinical anomalies that others miss.

Cross-Disciplinary Communication: Ability to translate complex medical and legal jargon into clear, logical concepts that software engineers can easily understand.

Tech-Fluency: Highly comfortable working with modern digital tools, software platforms, and collaborative, remote project management environments.

Sprint Agility: Proven ability to work autonomously and manage time effectively across flexible, sprint-based contract cycles.

AI Curiosity: A strong interest in legal-tech innovation and a desire to help shape how AI safely automates complex reasoning tasks.

Flexible, Part-Time Contract: Structured around product sprint cycles (e.g., dedicated blocks of hours for dataset annotation and feature review).

Hours: Anticipated 20-30 hours per week to start, with potential to scale as our feature roadmap expands.

Compensation: Competitive hourly/contract rate commensurate with experience.