Job Description

Responsibilities

• Build and operate systems across signup, payments, and usage to detect abuse and fraud.
• Own the technical enforcement pipeline from detection and human review through restrictions across platform systems.
• Build internal investigation and enforcement tools, including case queues, evidence summaries, bulk review, enactment, and alerting.
• Develop inference-path content-safety solutions, illegal-content reporting, and KYC or external-intelligence integrations.
• Create detection heuristics, monitoring, analytics, and risk systems that enable scalable enforcement and reduce false positives.
• Investigate incidents in data and collaborate with data scientists on risk and abuse ML models.
• Set technical direction and define reusable abuse-prevention patterns for other engineers.

Requirements

• 4+ years of experience building and operating production systems, ideally in trust and safety, fraud, payments risk, security, or anti-abuse.
• Proficiency in React, TypeScript, Next.js, and JavaScript runtimes.
• Ability to write SQL against large event datasets and reason about base rates, precision, recall, and decision costs.
• Strong judgment with incomplete evidence, high agency, and comfort shipping in a small, fast-moving environment.
• Discretion and resilience when reviewing disturbing content or handling sensitive user data.
• Strong written and verbal communication skills for explaining incidents, detection rules, and systems.
• Motivation to solve evolving adversarial problems.
• Preferred experience with Stripe Radar, chargebacks and disputes, crypto payment risk, identity and KYC systems, LLM-specific abuse, large-scale analytical datastores, observability platforms, hosted-AI reporting and compliance, or AI infrastructure and developer-tooling projects.

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