AI Product Manager - Commercial Lending

Job Description

AI Product Manager – Commercial Lending

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Role Overview

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We are looking for an experienced AI Product Manager with strong commercial lending domain expertise to identify, design, and deliver AI-enabled products that transform the commercial lending lifecycle.

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The role sits at the intersection of commercial lending, product management, data and AI . You will work closely with relationship managers, credit and underwriting teams, lending operations, risk and compliance stakeholders, data scientists, designers and engineers to identify high-value opportunities and translate them into scalable AI products.

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The ideal candidate understands both how commercial lending works end-to-end and how modern AI—including generative AI, agentic workflows, machine learning and document intelligence—can improve decision-making, productivity, customer experience and operational efficiency.

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Key Responsibilities

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Product Strategy & Opportunity Identification

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• Own product strategy and roadmap for AI-enabled capabilities across the commercial lending lifecycle.
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• Identify and prioritize opportunities based on business value, feasibility, risk and user impact.
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• Develop business cases and define measurable outcomes including cycle-time reduction, productivity improvement, risk reduction, revenue impact and customer experience.
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• Translate lending pain points into well-defined AI product opportunities rather than treating AI as a technology-first initiative.
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• Partner with business and technology leaders to move successful AI experiments from pilot to scaled production products.
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Commercial Lending Transformation

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Identify and develop AI solutions across areas such as:

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• Prospecting and relationship-manager intelligence
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• Loan origination and application intake
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• Financial spreading and borrower financial analysis
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• Credit assessment and underwriting
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• Credit memo preparation and review
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• Covenant extraction and monitoring
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• Loan documentation and document intelligence
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• Collateral analysis
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• Due diligence and exception management
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• Portfolio monitoring and early-warning signals
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• Annual reviews and credit renewals
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• Loan servicing and operations
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• Policy, procedure and credit-guideline intelligence
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Understand dependencies across relationship management, credit, underwriting, operations, risk, compliance and servicing when designing solutions.

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AI Product Management

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• Translate business problems into product requirements, user journeys, epics, stories and acceptance criteria.
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• Determine when to apply traditional automation, machine learning, generative AI, agentic AI or combinations of these approaches.
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• Work with AI/ML engineers, data scientists and architects to define solution approaches and evaluate technical feasibility.
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• Design human-in-the-loop workflows appropriate for regulated lending decisions.
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• Define evaluation frameworks for AI products, including accuracy, hallucination risk, explainability, latency, cost and business outcomes.
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• Establish feedback loops to continuously improve AI product performance.
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• Understand the implications of model choice, retrieval-augmented generation, enterprise knowledge, data quality and AI orchestration on product design.
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Responsible AI, Risk & Controls

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• Ensure AI products operate within commercial lending risk-management and regulatory requirements.
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• Partner with credit risk, model risk, compliance, legal, information security and data governance teams.
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• Incorporate traceability, explainability, auditability and human oversight into product requirements.
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• Clearly distinguish between AI that assists a lending professional and AI involved in credit or other consequential decision-making.
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• Define appropriate controls, escalation mechanisms and monitoring for AI-enabled workflows.
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Product Delivery & Adoption

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• Lead products from discovery and prototype through MVP, production deployment and scale.
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• Conduct user research with relationship managers, underwriters, credit officers and lending operations teams.
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• Establish product KPIs and measure adoption, business value and user satisfaction.
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• Drive change management and adoption by embedding AI capabilities into existing lending workflows rather than creating disconnected tools.
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• Partner with engineering teams using agile product-development practices.
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Required Experience

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• 7+ years of product management, banking transformation or financial-services technology experience , with meaningful experience owning digital or data products.
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• 3+ years of direct commercial lending experience or significant experience delivering products for commercial lending organizations.
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• Strong understanding of the commercial lending lifecycle from origination through underwriting, closing, servicing and portfolio management.
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• Working knowledge of areas such as financial spreading, credit analysis, credit memos, covenants, collateral, loan documentation and portfolio monitoring.
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• Experience working with lending platforms, banking data and complex enterprise workflows.
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• Demonstrated experience taking products from problem discovery through production and adoption.
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• Experience partnering with business, engineering, design, data and risk/control functions.
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AI & Technology Experience

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Candidates should have practical experience delivering products using one or more of the following:

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• Generative AI / Large Language Models
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• AI agents and workflow automation
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• Retrieval-Augmented Generation (RAG)
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• Document intelligence / intelligent document processing
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• Machine learning and predictive analytics
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• Enterprise search and knowledge management
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• APIs and enterprise data integration
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Deep hands-on model development is not required , but the candidate must be technically fluent enough to make product decisions and effectively work with AI architects, engineers and data scientists.

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Preferred Qualifications

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• Experience within commercial banking, corporate banking, middle-market lending or specialty lending.
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• Experience with commercial loan-origination or servicing platforms.
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• Familiarity with banking regulatory, model-risk and responsible-AI requirements.
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• Experience delivering AI products within a highly regulated enterprise.
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• Experience modernizing lending processes that depend heavily on documents, unstructured data and manual analysis.
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• Experience defining ROI and value realization for AI initiatives.
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What Success Looks Like

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Within the first 6–12 months, this person should be able to:

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• Develop a clear map of the commercial lending journey and its highest-value AI opportunities.
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• Build a prioritized AI product roadmap tied to measurable business outcomes.
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• Launch initial AI products with strong adoption among lending professionals.
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• Demonstrate measurable improvements in areas such as underwriting productivity, credit-review cycle time, operational effort or portfolio insight.
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• Establish a repeatable approach for taking commercial lending AI use cases from experimentation to production.
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• Build credibility with both senior commercial lending stakeholders and AI/engineering teams.
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