Join a high-impact team at the forefront of global compliance innovation, where you'll shape how Amazon navigates complex regulatory landscapes across international markets. As we scale marketplace facilitator obligations across various jurisdictions, we're building the future of fraud and abuse detection in the tax compliance context—orchestrating real-time risk detection to catch sophisticated fraud patterns, and creating adaptive governance frameworks that stay ahead of evolving regulations. You'll lead the development of core capabilities (e.g. holistic risk detection across tax, compliance and general bad actor abuse), partner with operations and tech partners, and coordinate regional leaders to solve unprecedented challenges at the intersection of policy, technology, and seller experience. This is your opportunity to drive decisioning that protects both Amazon and millions of sellers while building systems that set industry standards for compliance excellence.
Key job responsibilities The Tax Compliance Operations team is seeking an exceptional Senior Program Manager to drive cross-organizational initiatives that detect, prevent, and disrupt sophisticated tax fraud schemes across Amazon's marketplace. This role operates in high ambiguity, requiring you to manage stakeholders across 5+ VP organizations, and deliver measurable outcomes that protect Amazon and our customers. This role sits at the critical intersection of tax compliance, fraud detection, and product innovation as we transform Amazon's approach from reactive compliance to proactive risk intelligence, with exposure to technical and science product development, and cross-functional leadership to combat bad actor fraud and abuse and improve compliance risk controls.
Drive alignment across competing priorities and organizational boundaries to deliver unified fraud prevention strategies
Establish governance mechanisms including monthly cross-organizational reviews, decision frameworks, and escalation paths Manage complex dependencies across multiple development teams, investigation units, and policy organizations
Develop metrics and dashboards that track fraud trends, investigation outcomes, detection model efficacy, and time-to-implementation for investigation-driven improvements
Lead incident response for high-impact fraud events, coordinating cross-functional teams to contain exposure and rapidly deploy preventive measures
Stakeholder Management & Communication such as presenting program status, risks, and strategic recommendations to VP-level audiences across multiple organizations; facilitating decision-making forums that resolve cross-functional conflicts and drive consensus on contentious trade-offs; Translating technical complexity into business impact for executive audiences and business requirements into technical specifications for engineering teams
Basic Qualifications
- 5+ years of program or project management experience
- Experience using data and metrics to determine and drive improvements
- Experience owning program strategy, end to end delivery, and communicating results to senior leadership
- Experience delivering results for large, cross-functional initiatives/projects
- Experience managing technical programs across cross-functional teams, building processes and coordinating release schedules
- • Demonstrated ability to drive consensus and make decisions in high-ambiguity environments
- • Strong analytical skills with experience defining metrics, building business cases, and quantifying program impact
- • Excellent written and verbal communication skills, including executive-level presentations
- • Track record of delivering results despite organizational complexity and resource constraints
Preferred Qualifications
- Experience working in risk, fraud or compliance organizations
- Experience communicating and handling cross-functional programs including project stakeholders, technical program managers, and software development teams
- • Background in tax compliance, regulatory programs, or financial crime prevention
- • Familiarity with data analysis, machine learning concepts, or technical system design
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