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Description

Are you passionate about building proactive systems that protect brands before infringement reaches customers? We're seeking a Senior Program Manager who will drive Amazon's IP discovery and enablement systems — the intelligence and preparation layer that determines whether downstream detection can succeed at scale.

In this role, you'll own the end-to-end program lifecycle for RANGER's three pillars: Brand and IP Discovery (identifying which brands need protection), IP Enablement (building the machine-readable knowledge infrastructure that makes detection possible), and ASIN Discovery (continuously scanning billions of listings to surface candidates for evaluation). Your work addresses the recurring root cause of IP protection gaps where majority of detection defects trace back to missing or incomplete IP knowledge — the problem this team exists to solve.

This position shapes what Amazon protects and how fast we can protect it. You'll partner with applied scientists on risk scoring models and agentic AI collection systems, manage IP knowledge completeness programs across trademark, copyright, and design patent categories, drive prioritization strategies that route resources to the highest-risk gaps, and coordinate the formal handoff contract between Discovery and Detection. Your decisions compound across marketplaces, IP types, and brand tiers as you build the infrastructure that every downstream IPP system depends on.

Key job responsibilities
• Drive IP enablement programs that build and maintain machine-readable IP knowledge at scale: managing collection pipelines (automated agentic AI, patent office APIs, structured human research), tracking IP object completeness across text, logo, copyright, and design patent types, and closing the coverage gaps that account for the majority of downstream detection failures.
• Own brand risk scoring and prioritization programs that identify which brands need protection before infringement occurs, managing risk models processing millions of brands across all marketplaces and routing high-priority IP gaps to collection treatments based on residual risk.
• Drive ASIN discovery pipeline programs that continuously scan billions of catalog listings through multiple trigger types, managing the filtering, de-duplication, and tiered prioritization systems that determine which ASINs flow to Detection for evaluation.
• Conduct root cause analysis on protection gaps — classifying defects into collection problems, policy gaps, model misses, and anchor failures — and translate findings into systematic program improvements with measurable targets tied to top-line NOI reduction goals.
• Present strategic recommendations to Directors and VPs on discovery and enablement system performance, establishing metrics that frame IP knowledge completeness as infrastructure health (not just enrollment counts), and driving cross-team alignment on the formal handoff contract with Detection.

A day in the life
Your day begins by reviewing IP enablement pipeline health. You'll meet with applied scientists to evaluate a risk model iteration that changes how brands get prioritized for IP collection, weighing coverage breadth against collection pipeline capacity. You will review spikes in brand-filed complaints back to an IP enrollment gap — then build a program plan to prevent bottlenecks. You'll coordinate with Detection on the formal handoff contract: confirming that IP facts in the knowledge repository are being consumed downstream, and tracking ASINs that failed detection due to missing IP context. You'll wrap up by presenting to leadership on how closing IP coverage for a specific brand tier could prevent thousands of complaints per quarter — framing it as infrastructure readiness, not reactive enrollment.

About the team
The brand protection program team serves as Amazon's systemic problem-solving engine, providing vertical product-program support across discovery, detection, and remediation systems.

Product and engineering teams explicitly prefer working with our team because we deliver detailed blueprints instead of vague problems, enabling engineering to build to specification and validate against clear success criteria.