Senior Product Manager - AI Products

New

JobgetherFinancial technology

Based in the United StatesFull-TimeSenior

SalaryAnnual base salary range of $138,667–$197,000 USD, with additional bonus opportunities.

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Job Details

Have 5+ years of product management experience, with a track record of delivering enterprise AI/ML products in a B2B SaaS environment.
Have experience taking AI-powered features from concept to production, including model integration, data contracts, and post-launch monitoring.
Understand digital product development, including conversational AI, generative AI, automation, and data-driven platforms.
Be familiar with AI/ML concepts, large language models (LLMs), Model Context Protocol (MCP), generative AI platforms, and API integrations.
Know responsible AI principles, model interpretability, bias mitigation, and quality and accuracy metrics for production-grade AI systems.
Have experience partnering with Data Science and Engineering teams on training data requirements, model performance, and iterative feedback loops.
Have experience conducting customer research, user discovery, and usability testing and translating insights into product strategy.
Be proficient in AI-driven prototyping methods and understand emerging AI-assisted software development practices.
Have strong knowledge of agile methodologies, product management processes, and delivery artifacts.
Have a bachelor's degree; an MBA is preferred.
Consumer lending or mortgage software experience is a strong plus.

Own the product strategy and roadmap for AI-powered automation capabilities across the platform.
Define measurable product outcomes and ensure roadmap initiatives deliver against them.
Identify automation opportunities in loan origination and account opening workflows.
Conduct discovery with lending operations teams, compliance professionals, technology buyers, and other stakeholders.
Translate research, product usage data, and competitive intelligence into product opportunities.
Lead cross-functional execution with Engineering, Data Science, and Design teams using agile methodologies.
Translate business requirements into product epics, user stories, acceptance criteria, and documentation.
Collaborate with Data Scientists and Machine Learning Engineers to scope model development and define performance metrics.
Coordinate with Legal, Compliance, and Information Security teams on regulatory requirements.
Own launch readiness and monitor post-launch KPIs, feedback, model errors, and product performance.

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