Senior Product Manager – AI Products

Role Overview

• Own the end-to-end product strategy and roadmap for AI automation features within the platform.
• Define measurable outcomes (efficiency gains, error reduction, decision accuracy) and hold the roadmap accountable to them.
• Partner with executive leadership to align AI initiatives with company-wide product vision and revenue goals.
• Build business cases justifying R&D investment based on expected revenue opportunities.
• Identify high-value automation opportunities across the loan origination and account opening lifecycles.
• Stay updated with the latest trends and advancements in AI and ML, to identify opportunities for innovation and incorporate relevant insights into product strategy and development.
• Conduct deep discoveries with lending operations teams, compliance officers, and technology buyers to surface unmet needs. Dig beyond stated needs to define innovative solutions to customer challenges.
• Synthesize qualitative research, quantitative usage data, and competitive intelligence into clear product opportunities.
• Build and maintain a robust feedback loop with design partners and early-access customers during feature development.
• Drive execution with engineering, data science, and design teams using agile practices and emerging Dev AI practices.
• Translate business needs into clear and actionable epics, user stories, acceptance criteria, and supporting documentation. Lead rapid prototyping exercises to speed time to market and enable early customer validation.
• Ensure requirements align with strategic business goals while balancing compliance, security, scalability, and technical feasibility.
• Partner with data scientists and ML engineers to scope model development, define success metrics, and establish human-in-the-loop review processes.
• Coordinate with compliance, legal, and information security to ensure AI features meet regulatory expectations (FCRA, ECOA, fair lending, model risk management, emerging regulation governing AI use in fintech).
• Own launch readiness: go-to-market coordination, documentation, training, and customer communication.
• Define and track KPIs for AI features post-launch: automation rates, exception volumes, model drift indicators, and business impact.
• Establish feedback mechanisms that surface edge cases and model errors quickly and translate them into iteration cycles.
• Communicate product performance transparently to leadership and stakeholders.
• Collaborate with Sales and Marketing to track product pipeline development and revenue opportunity. Correct course where adoption falls short of expectation.

Requirements

• 5+ years’ experience in product management, with proven success designing enterprise AI/ML products in a SaaS B2B environment.
• Experience conducting customer/user research, usability testing, and translating insights into product strategy. Proficiency with AI-driven prototyping methods.
• Strong organizational and multi‑tasking abilities, capable of managing multiple projects, priorities, and communication channels in a fast‑paced environment
• Mastery of agile methodologies, processes, artifacts. Understanding of/exposure to emerging DevAI practices.
• Strong problem-solving skills
• Effective storytelling and presentation abilities
• Excellent collaboration skills within and across teams
• Ability to give and receive constructive design feedback
• Awareness of industry trends, emerging technologies, and best practices in AI product design.
• Demonstrated track record of taking AI features from concept to production—including model integration, data contracts, and post-launch monitoring.
• Expertise in digital product development, including conversational AI, GenAI, automation, and data-driven platforms.
• Familiarity with AI/ML concepts, LLMs, MCPs, GenAI platforms, API integration.
• Familiarity with responsible AI principles, model interpretability, bias mitigation, and quality/accuracy metrics required for production grade AI systems.
• Experience collaborating with Data Science and Engineering teams to define training data needs, evaluate model performance, and implement iterative feedback loops.
• Bachelor’s degree required; MBA preferred. Computer science background (education or other demonstrated proficiency) preferred.

Benefits

• Insurance coverage (medical, dental, vision, life, and disability)
• Flexible paid time off
• Paid holidays
• 401(k) plan with company match
• Remote work