AI Product Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Take ownership of a rolling six-to-twelve-month AI roadmap that focuses on extraction coverage, accuracy, and the foundational platform; align it with team capacity, manage sequencing dependencies, adjust plans as new evidence emerges, and represent it in portfolio planning.

• Gather and prioritize requests for new document types, forms, and fields utilizing robust frameworks like RICE, WSJF, Kano, opportunity scoring, and voice-of-customer analysis.

• Ensure that prioritized items encompass definitions and test data necessary for validation and communicate prioritization rationale to stakeholders.

• Define and report on accuracy metrics for executives, customers, Product, and Engineering teams.

• Convert model-level metrics such as per-field precision, coverage, and straight-through rate into user outcomes, including missed data, user corrections, and interactions required for filing-ready results.

• Manage the recurring accuracy report.

• Provide product requirements for model and vendor selections, including customer-relevant accuracy, cost, and latency thresholds, as well as business cases, budgets, and acceptance criteria for releases.

• Keep comprehensive decision records for model and vendor selections.

• Strategically plan engineering reserves around filing peaks from September to November and oversee the scope and timelines for the January tax-year release.

• Establish defect-intake service levels in collaboration with Client Success and QA, while ensuring proof-of-concept work remains time-boxed.

• Collaborate with product managers and UX to transform user corrections into field-level provenance signals and foster a confidence-driven review experience.

⛳️ Requirements

• A minimum of 4 years in product management for shipped B2B software, preferably in fintech or regtech, where inaccuracies can be more costly than delays, with at least 2 years managing an AI/ML-powered product surface such as document AI or extraction, search and ranking, LLM features, or an ML platform.

• Proficient in the fundamentals: capacity planning in alignment with real team dynamics, prioritization frameworks (RICE, WSJF, Kano, voice-of-customer synthesis), roadmap sizing, release management, and creating PRDs that engineers will find useful.

• Comprehend how ML products encounter failures distinct from traditional software: understand precision and recall trade-offs, evaluation sets, drift, cost per inference, and recognize that "the model got it wrong" is primarily a product concern.

• Experience in making or influencing decisions on building, buying, or replacing model or vendor components, and able to discuss a past decision that did not go well.

• Capable of clear writing and conducting efficient meetings. A significant aspect of this role involves converting engineers' insights into actionable decision documents for Product, Tax, and Finance teams.

• While tax-domain expertise is not necessary, curiosity is essential; the intriguing failure modes often reside in the footnotes, as Tax Content manages the rules and CPAs adjudicate.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible work hours and remote work options.

• Opportunities for professional development and continuous learning.

• Engaging work environment with a focus on innovation and teamwork.