Senior Product Manager, MeridianLink
AI Platform
$94.7-161.4k
Kafka
Kinesis
Senior and Expert level
Remote from US
Digital lending platform for every financial institution
Open for applications
Digital lending platform for every financial institution
501-1000 employees
FintechB2BMortgagesLendingFinancial Services
Open for applications
$94.7-161.4k
Kafka
Kinesis
Senior and Expert level
Remote from US
501-1000 employees
FintechB2BMortgagesLendingFinancial Services
Company mission
To accelerate and simplify workflows while helping community financial institutions grow, scale and serve their consumers and communities.
Role
Who you are
- We are seeking a strategic and technically fluent Senior Product Manager to own the AI platform layer that underpins our vertical SaaS offering for the lending industry
- You have hands-on familiarity with how production of AI systems are built and operated. You can hold a meaningful technical conversation with an ML engineer about inference latency and embedding strategies — and translate those tradeoffs into crisp product decisions
- You have shipped platform capabilities, not just features, and you understand the difference: versioned APIs, backward compatibility, SLA contracts, and developer experience are as important to you as end-user outcomes
- Candidates with prior experience building software for consumer lending or mortgage—LOS platforms, automated underwriting, document intelligence, or decisioning engines—will move to the top of the queue. Deep domain familiarity shortens the runway to credibility with both engineering and go-to-market teams
- 5+ years’ experience in product management, with proven success designing enterprise AI/ML products in a SaaS B2B environment
- At least 3 years in a platform, infrastructure, or developer tools
- 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 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
- Experience 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
- Proven track record shipping AI or ML capabilities into production: you have written PRDs that specify inference APIs, data schemas, latency budgets, model versioning strategies, and observability requirements
- Sufficient technical depth to participate in architecture discussions with Engineering
- Hands-on familiarity with at least one modern AI/ML stack, vector databases, and model serving infrastructure
- Experience defining API contracts and SDK developer experiences—including versioning strategies, deprecation policies, and changelog communication
- Comfort working with data engineering concepts: ETL/ELT pipelines, feature stores, schema registries, event streaming (Kafka, Kinesis), and data quality frameworks
- Strong written communication skills for technical audiences
- Bachelor’s degree required; MBA preferred. Computer science background (education or other demonstrated proficiency) required
- Consumer or mortgage lending software experience is a plus; experience in vertical SaaS required
What the job involves
- You are responsible for the foundational capabilities—model serving infrastructure, data pipelines, APIs, SDKs, and developer tooling—that enable both internal engineering teams and, in select cases, external integrators to build AI-powered experiences on top of our platform
- Own the end-to-end product strategy and roadmap for the AI platform layer
- 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 benefits
- Partner with principal engineers and ML infrastructure leads to make informed build-vs-buy-vs-partner decisions on foundational AI capabilities
- Establish and govern platform-level standards: API versioning policies, model lifecycle management, prompt versioning, and observability requirements
- 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
- Treat internal R&D teams as your primary customers. Conduct structured discovery with feature teams to understand their AI integration pain points, latency requirements, and data access needs
- Define and own the developer experience for consuming the AI platform: API contracts, SDK design, documentation standards, sandbox environments, and onboarding flows
- Establish a platform roadmap governance process: intake, prioritization, and communication of platform changes to dependent teams
- Build feedback loops with consuming teams post-release to detect friction, integration failures, and unmet capability needs early
- Establish monitoring and observability standards: model drift detection, confidence thresholds, input distribution shifts, and alerting policies
- Translate regulatory requirements for AI use in lending (FCRA, ECOA, HMDA, OCC SR 11-7 model risk management) into concrete platform requirements: explainability APIs, audit logging, adverse action reason codes, and human-in-the-loop override mechanisms
- Partner with information security to define data residency, encryption-at-rest/in-transit requirements, and PII handling policies for AI data flows
- Maintain a clear capability matrix of which AI features are permissible for which customer tiers, regulatory environments, and data sensitivity levels
- Define and own platform-level SLOs: inference availability, P99 latency, pipeline throughput, and data freshness
- Build platform health dashboards and escalation playbooks for AI service degradation—distinct from application-layer monitoring
- Track platform adoption metrics: number of consuming teams, API call volumes, feature flag usage, and time-to-integrate for new consumers
- Hold regular platform reviews with engineering leadership to surface technical debt, capacity constraints, and architectural risks before they affect downstream feature teams
- Align platform metrics with those of the AI-based application products; collaborate with application Product Managers to ensure alignment
Our take
MeridianLink provides modern software platforms for financial institutions and consumer reporting agencies. Specifically, it powers digital lending and account opening for the former and data verifications for the latter.
The company has been trusted for over 20 years and has remained adaptable and open to change with the industry, such as its recent addition of engagement features that offer new ways to help financial services drive growth, reach target audiences and adjust campaigns to meet business and customer needs. It has therefore maintained a number of impressive customers, from BankPlus and American United to FirstBank and TwinStar.
Building on this track record, MeridianLink was recently acquired by Centerbridge Partners, marking an important step forward. Going private in this $2B deal gives the company flexibility to accelerate innovation, expand its platform, and leverage AI and data more effectively. With Centerbridge's support, MeridianLink is in a good position to strengthen its competitive edge and continue helping financial institutions grow in a rapidly evolving market.
Freddie
Company Specialist at Welcome to the Jungle
Insights
1% employee growth in 12 months
Company
Company benefits
- Ongoing development: Continuous learning is essential to growth, and we’re committed to helping our employees thrive. You’ll have the opportunity to take part in job-specific training, monthly soft-skill sessions, and leadership classes designed to support your development at every stage.
- Access to executives: Have a good idea? Share it with peers, managers, or executives. Our leadership is approachable and actively involved in supporting your work.
- Health lifestyle: Healthy staff makes us happy. We support our team members with resources and programs that promote financial, physical, and mental health—encouraging balance, self-care, and a lifestyle that helps you feel your best every day.
- Celebrations: All work and no play makes for a dull day. We celebrate holidays, birthdays, work anniversaries, and other milestones with fun activities that bring us together. We also provide channels for employees to recognize and celebrate each other’s achievements, making appreciation a regular part of our culture.
- Community partnering: Take a day off with pay to volunteer where it matters most to you or join the company in various community service projects throughout the year.
Company HQ
Irvine Technology Center, Irvine, CA
Leadership
Larry Katz
(CEO)Larry joined MeridianLink in 2023 as CFO and became CEO in 2025. Prior to this, they were the CFO at StubHub and Genesys as well as a Managing Director at JPMorgan Chase & Co. for 15 years.
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