AI Product Manager - Commercial Lending

AI Product Manager – Commercial Lending

Role Overview

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.

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.

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.

Key Responsibilities

Product Strategy & Opportunity Identification

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

Commercial Lending Transformation

Identify and develop AI solutions across areas such as:

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

Understand dependencies across relationship management, credit, underwriting, operations, risk, compliance and servicing when designing solutions.

AI Product Management

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

Responsible AI, Risk & Controls

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

Product Delivery & Adoption

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

Required Experience

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

AI & Technology Experience

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

• Generative AI / Large Language Models
• AI agents and workflow automation
• Retrieval-Augmented Generation (RAG)
• Document intelligence / intelligent document processing
• Machine learning and predictive analytics
• Enterprise search and knowledge management
• APIs and enterprise data integration

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.

Preferred Qualifications

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

What Success Looks Like

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

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