Senior Product Manager - AI Platform (FinTech)

MeridianLink, Inc.

Job Overview

Location

US Remote

Job Type

Full-time

Full Job Description

📋 Description

• Own the end-to-end product strategy and roadmap for the AI platform layer that underpins MeridianLink’s vertical SaaS offering for the lending industry.
• Build foundational AI capabilities including model serving infrastructure, data pipelines, APIs, SDKs, and developer tooling used by internal engineering teams and select external integrators.
• Translate regulatory requirements for AI in lending (FCRA, ECOA, HMDA, OCC SR 11-7) into platform requirements such as explainability APIs, audit logging, adverse action reason codes, and human-in-the-loop override mechanisms.
• Establish and govern platform-level standards: API versioning policies, model lifecycle management, prompt versioning, and observability requirements.
• Treat internal R&D teams as primary customers; conduct structured discovery to understand AI integration pain points, latency requirements, and data access needs.
• Define and own the developer experience for consuming the AI platform, including API contracts, SDK design, documentation standards, sandbox environments, and onboarding flows.
• Establish a platform roadmap governance process for 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.
• 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 teams.
• Align platform metrics with those of AI-based application products and collaborate with application Product Managers to ensure alignment.
• Partner with principal engineers and ML infrastructure leads to make informed build-vs-buy-vs-partner decisions on foundational AI capabilities.
• Establish monitoring and observability standards: model drift detection, confidence thresholds, input distribution shifts, and alerting policies.
• 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.
• Stay updated with the latest trends and advancements in AI and ML to identify innovation opportunities and incorporate insights into product strategy.
• Ship platform capabilities—not just features—with emphasis on versioned APIs, backward compatibility, SLA contracts, and developer experience.
• Write PRDs that specify inference APIs, data schemas, latency budgets, model versioning strategies, and observability requirements.
• Collaborate with Data Science and Engineering teams to define training data needs, evaluate model performance, and implement iterative feedback loops.
• Work with data engineering concepts: ETL/ELT pipelines, feature stores, schema registries, event streaming (Kafka, Kinesis), and data quality frameworks.
• Participate in architecture discussions with Engineering with sufficient technical depth to contribute meaningfully.
• Have 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.
• Demonstrate proficiency with agile methodologies, processes, and artifacts.
• Conduct customer/user research, usability testing, and translate insights into product strategy using AI-driven prototyping methods.
• Communicate effectively with technical and non-technical stakeholders through storytelling, presentations, and written documentation.
• Possess strong problem-solving skills and ability to give and receive constructive design feedback.
• Prior experience building software for consumer lending or mortgage—such as LOS platforms, automated underwriting, document intelligence, or decisioning engines—is highly valued.

🎯 Requirements

• 5+ years’ experience in product management with proven success designing enterprise AI/ML products in a SaaS B2B environment
• At least 3 years in platform, infrastructure, or developer tools
• Bachelor’s degree required; Computer science background (education or demonstrated proficiency) required
• Experience shipping AI or ML capabilities into production, including model integration, data contracts, and post-launch monitoring
• Familiarity with AI/ML concepts, LLMs, GenAI platforms, API integration, and responsible AI principles
• Experience working with data engineering concepts: ETL/ELT pipelines, feature stores, schema registries, event streaming (Kafka, Kinesis)

🏖️ Benefits

• Remote work opportunity across the United States
• Exposure to cutting-edge AI platforms in a high-growth FinTech vertical
• Collaboration with principal engineers and ML infrastructure leads on foundational AI systems
• Direct impact on regulatory-compliant AI products used in consumer lending and mortgage industries

Skills & Technologies

REST

Kafka

Product Management

Senior

Remote

Degree Required

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MeridianLink, Inc.

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About MeridianLink, Inc.

MeridianLink provides cloud-based software for banks, credit unions, and mortgage lenders to manage loan origination, account opening, credit reporting, and deposit products. The platform automates underwriting workflows, integrates with credit bureaus and core banking systems, and offers analytics for risk management and regulatory compliance. Customers use the APIs and configurable modules to streamline consumer, small-business, and mortgage lending operations while ensuring data security and audit standards.

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