Join a pioneering team leveraging machine learning and generative AI to revolutionize accounting for Amazon's vast transportation network. This role offers the unique opportunity to apply cutting-edge AI to a domain where precision directly impacts financial outcomes. You will lead the development of software solutions that automate anomaly detection, root cause analysis, and financial reconciliation processes, transforming month-end closing from a manual investigation into a continuous, automated certification.

As a leader, you'll guide a talented engineering team, own the strategic roadmap in collaboration with product management and accounting stakeholders, and ensure the operational excellence of services at Amazon's scale. You will be instrumental in establishing best practices for integrating AI into controlled financial processes, ensuring auditability and compliance.

Manage and grow a high-performing team of engineers, fostering their development through challenging technical problems. Own the technical roadmap for your area, partnering closely with Product Management, Accounting, and Controllership teams. Drive operational excellence for your services, focusing on load, security, resiliency, and compliance. Champion the integration of AI into financial processes, implementing robust audit trails, approval workflows, and separation of duties. Develop and deploy machine learning models for anomaly detection in reconciliation and financial data. Build generative AI agents to identify the root cause of financial breaks and propose automated fixes. Create a generative AI assistant to provide insights and answer financial variance questions. Automate standard operating procedures for financial close using AI-driven authoring and execution.

A minimum of 8 years in defining and developing multi-tier web services. Possess at least 3 years of experience managing engineering teams. Accumulate over 7 years of overall engineering experience. Demonstrated experience partnering effectively with product or program management teams. Solid understanding of engineering practices across the full software development lifecycle, including coding standards, code reviews, source control, build processes, testing, and operations. Proven experience in designing or architecting new and existing systems, with knowledge of design patterns, reliability, and scaling.