AI Product Manager

🕒 il y a 27 jours

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

✅ Responsable Produit

🗣️🇺🇸🇬🇧 Anglais requis

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K1X

11 - 50 employés

💼 Conseil

🏥 Santé

⚖️ Juridique

Consulting • Healthcare • Legal

K1X est une plateforme alimentée par l'IA qui se spécialise dans la rationalisation de la conformité fiscale des investissements alternatifs pour les investisseurs et les conseillers. La plateforme propose diverses solutions automatisées, y compris K1 Aggregator pour automatiser la réception et l'analyse des données du formulaire K-1, K1 Creator pour la production numérique des formulaires K-1, et 990 Tracker pour automatiser le rapport et le dépôt des dossiers exemptés. K1X utilise une technologie IA brevetée pour garantir une haute précision et réduire le temps d'extraction manuelle des données. Elle est conçue pour améliorer l'efficacité, réduire les coûts et renforcer la transparence dans les processus fiscaux, en particulier en ce qui concerne les investissements alternatifs.

Description

• Own a rolling six-to-twelve-month AI roadmap for extraction coverage, accuracy, and the underlying platform; size it against team capacity, sequence dependencies, re-plan as evidence changes, and represent it in portfolio planning. • Intake and prioritize requests for new document types, forms, and fields using defensible frameworks such as RICE, WSJF, Kano, opportunity scoring, and voice-of-customer synthesis. • Ensure prioritized items include definitions and test data needed for validation, and explain prioritization decisions to stakeholders. • Own how accuracy is defined and reported for executives, customers, Product, and Engineering. • Translate model-level measures such as per-field precision, coverage, and straight-through rate into user outcomes, including missed data, user corrections, and touches needed for filing-ready results. • Own the recurring accuracy report. • Provide product requirements for model and vendor decisions, including customer-relevant accuracy, cost, and latency thresholds, business cases, budgets, and release acceptance criteria. • Maintain decision records for model and vendor choices. • Plan engineering reserve around September–November filing peaks and own scope and dates for the January tax-year release. • Set defect-intake service levels with Client Success and QA, and keep proof-of-concept work time-boxed. • Partner with product managers and UX to turn user corrections into field-level provenance signals and a confidence-driven review experience.

🎯 Exigences

• 4+ years of product management on shipped B2B software, ideally fintech or regtech where a wrong number costs more than a slow one, with at least 2 years owning an AI/ML-powered product surface: document AI or extraction, search and ranking, LLM features, or an ML platform. • Fluent in the mechanics: capacity planning against a real team, prioritization frameworks (RICE, WSJF, Kano, voice-of-customer synthesis), roadmap sizing, release management, and PRDs an engineer would actually read. • Understand how ML products fail differently from software: precision and recall trade-offs, evaluation sets, drift, cost per inference, and why "the model got it wrong" is a product question first. • Have made or shaped build, buy, or replace calls on model or vendor components, and can walk through one that went badly. • Write clearly and run a tight meeting. Half this job is turning engineers' conviction into a decision document Product, Tax, and Finance can act on. • Tax-domain knowledge is not required; Tax Content owns the rules and CPAs adjudicate. Curiosity is; the interesting failure modes live in the footnotes.

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