Principal Product Manager Tech - Credit and Fraud Risk, Amazon B2B Payments and Lending

About the role

The Amazon Business Payments & Lending (ABPL) team provides invoicing, working capital, and payment acceptance solutions to Amazon Business customers, sellers, and other small business customers across Amazon. We are part of the global Amazon Payments organization, which aims to delight our customers by building payment experiences and financial services that are trusted, valued, and easy to use from anywhere in any way.

Responsibilities

• Own the 3-5 year strategic product vision and roadmap for credit and fraud risk management, defining what to build, why it matters, and how to measure success across a multi-billion dollar lending portfolio
• Drive innovation through Generative AI and AI agents — identify and deliver use cases where foundation models, autonomous agents, and intelligent automation can transform credit decisioning, fraud detection, and risk operations
• Architect AI-native product solutions for real-time credit underwriting, dynamic line management, fraud pattern recognition, and automated risk remediation
• Set the technical product strategy for how AI capabilities (GenAI, ML models, agents) integrate into credit and fraud systems — evaluating which AI approaches will become competitive necessities and shaping platform architecture accordingly
• Drive clarity in high-ambiguity environments where the problem, opportunity, and strategy are undefined — distill diverse inputs from regulators, risk teams, customers, and stakeholders into a coherent product vision
• Influence strategic direction across multiple VP-level organizations including Payments, Amazon Business, Technology, and Seller Partner Services through written narratives, PR/FAQs, and executive forums
• Partner with Science and Engineering leaders to evaluate emerging AI architectures, shape technical trade-offs, and ensure platform decisions today do not constrain strategic options tomorrow
• Establish metrics frameworks and experimentation strategies that measure the effectiveness of AI-driven risk decisions, including novel approaches to model explainability and fairness
• Actively recruit, mentor, and develop PM talent; contribute to the PM community through coaching, promotion assessments, and best-practice evangelism

Qualifications

• 10+ years of technical product or program management experience
• Bachelor's degree or above in computer science, engineering, mathematics or equivalent, or Bachelor's degree or above in business administration, finance, economics, computer science, data science, engineering, or other related field
• Experience delivering large, cross-functional, customer facing products
• Experience building cross-functional partnerships and influencing stakeholders across the organization to act without having a direct reporting relationship
• Experience building credit underwriting, fraud detection, or financial risk management products in fintech or financial services
• Hands-on experience defining product strategy for Generative AI, LLM-powered applications, or autonomous AI agent systems
• Experience owning and driving multi-year product strategy and vision across multiple teams and organizations, with demonstrated P&L impact
• Deep technical judgment — ability to evaluate complex engineering proposals, weigh technology alternatives, shape architecture decisions, and foresee long-term consequences of technical choices
• Experience with AI/ML product development — understanding of how machine learning models, large language models, and AI agents are designed, trained, deployed, and measured in production systems
• Strong executive communication skills — experience driving strategic narratives (PR/FAQs, OP1/OP2, investment cases) and presenting to Director/VP-level leadership
• Experience making high-stakes decisions with incomplete data, applying sophisticated judgment to balance customer value, business risk, and technical feasibility
• Track record of recruiting, mentoring, and developing product management talent