Description

We are looking for a Software Development Manager to lead a team of engineers building systems that protect Amazon's marketplace at scale. You will own the technical direction and delivery across seller lifecycle verification and inventory trust, hire and develop engineers, and partner with applied scientists, product managers, and risk operations teams to ship capabilities that directly reduce bad actor impact on customers and legitimate sellers.

Selling Partner Identify Verification's (SPIV) mission is to know who Amazon is doing business with. We build automated verification systems that prevent bad actors from entering Amazon's stores while creating friction-free experiences for legitimate selling partners across all worldwide marketplaces.

This role supports two business verticals within SPIV:

Seller Lifecycle Management (SLM) monitors and manages changes to selling partner accounts throughout their lifecycle, from post-registration through dormancy. Bad actors exploit the marketplace by trading verified accounts, managing multiple accounts to evade detection, and using compromised accounts for feedback manipulation, unauthorized drop-shipping, trademark violations, and fraud. SLM detects ownership changes, account compromise, and account trading patterns to maintain marketplace trust. The team includes Bad Actor Prevention (BAP), which re-verifies high-risk accounts, and Fraud Identification and Remediation Enforcement (FIRE), which conducts forensic analysis of seller accounts and implements targeted enforcement actions.

Inventory Trust (IT) safeguards Amazon's store from bad inventory and bad actors concealing their identities. The team prevents bad actors from using Amazon's fulfillment network to scale abuse, ensures counterfeit and illegal inventory is identified and destroyed, withholds funds from bad actors, prevents seller credit abuse, and disrupts bad actor "spare accounts." IT operates on the principle that while accounts and listings may be infinite, inventory is tangible, trackable, and finite, making it the key lever for disrupting the bad actor flywheel.


Key job responsibilities
- Lead, hire, mentor, and grow a team of 6-10 software engineers across SLM and IT problem spaces
- Own the technical roadmap, balancing new detection and enforcement capabilities with operational excellence and system reliability
- Design and build systems for account lifecycle monitoring, detecting ownership changes, account compromise, dormancy abuse, and account trading at scale
- Build inventory tracking and enforcement systems that prevent bad actors from using Amazon's fulfillment network and identify counterfeit/illegal inventory
- Partner with applied science teams to integrate ML models for risk scoring, account relationship detection, and fraud pattern identification into production systems
- Drive automation of investigation workflows, replacing manual review processes with automated decision systems that improve speed, accuracy, and cost
- Establish and maintain a high operational bar, own your team's on-call, drive COE follow-ups, and build resilient systems
- Make data-driven prioritization decisions, balancing customer safety, seller experience, and regulatory compliance
- Collaborate with cross-functional partners across SPIV (Related Accounts, Verification Services, Centralized Services) to share signals and coordinate enforcement

A day in the life
You inspect operational metrics each morning and triage issues with your on-call engineer. You challenge your team in design reviews, pushing them on failure modes, scalability, and durability against adapting adversaries. You pair with engineers on the hardest problems, not writing the code but ensuring the thinking is sound. You coordinate with partner teams across SPIV, applied scientists, and operations. You set up mechanisms, metrics reviews, operational standards, retrospectives, so the team continuously improves. Some days focus on hiring, others on operational events. The constant: technical depth, people development, and raising the bar.