Sr. Product Manager - AI Products

Role overview

Lead the strategy and delivery of AI automation for a business software platform serving lending and account-opening workflows. The role connects customer needs, product design, data science, engineering, and risk controls to bring reliable AI capabilities from discovery into production and measure their impact.

Responsibilities

- Set the roadmap for AI automation and define measurable goals such as reduced manual work, fewer errors, and improved decision accuracy. - Research lending operations and buyer needs, combining customer feedback, product usage, and market insights to identify opportunities. - Turn priorities into clear requirements, prototypes, and delivery plans with design, engineering, and data science teams. - Work with model teams on data needs, evaluation, human review, and ongoing monitoring; coordinate with compliance, legal, and security on regulatory expectations. - Prepare launches with customer guidance and internal enablement, then track adoption, exceptions, model performance, and business results. - Share performance with stakeholders and adjust plans when results or adoption fall short.

Requirements

- At least five years of product management experience, including successful delivery of enterprise AI or machine learning products in B2B SaaS. - Experience taking AI capabilities from concept to production, including model integration, data contracts, and post-launch monitoring. - Knowledge of AI/ML, generative and conversational AI, automation, APIs, and responsible AI practices such as bias mitigation and interpretability. - Experience conducting user research and usability testing, translating findings into product direction, and working with data science and engineering teams. - Strong agile delivery, prioritization, problem-solving, communication, and cross-functional collaboration skills. - Bachelor’s degree required; an MBA is preferred.

Nice to have

- Experience with consumer or mortgage lending software, computer science, or emerging AI-assisted development practices. - Familiarity with lending regulations and model risk considerations, including fair lending requirements.