Senior Product Manager - AI Products

MeridianLink

1d•$94,667 - $161,400

About The Position

We are looking for a seasoned Senior Product Manager to lead the definition and delivery of AI-powered automation capabilities within our vertical SaaS platform. This role sits at the intersection of financial services technology and applied AI and is accountable for translating complex lending workflows into intelligent, scalable product experiences that meaningfully reduce manual effort for our customers. You have shipped AI features in production—not just prototypes—and you understand what it takes to bring models, data pipelines, and UX together into a trustworthy, compliant product. Experience in consumer lending or mortgage software is a strong differentiator, as you will need to quickly earn credibility with domain-expert stakeholders and customers.

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.

Nice To Haves

MBA preferred.
Computer science background (education or other demonstrated proficiency) preferred.
Consumer or mortgage lending software experience is a plus

Responsibilities

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.