Software Engineer, Trust & Safety
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Job Description
Software Engineer building abuse, fraud, and content-safety systems for OpenRouter’s enterprise AI routing infrastructure. Owning detection, enforcement, review tooling, and risk analytics.
Responsibilities:
- Build and operate systems across signup, payments, and usage to detect abuse and fraud early
- Own the technical enforcement pipeline from detection through human review and restrictions across systems
- Build internal investigation and enforcement tools, including case queues, evidence summaries, bulk review and enactment, and investigation alerts
- Ship content-safety solutions on the inference path, including illegal-content detection and reporting
- Build or integrate KYC systems and external intelligence sources to detect and stop fraud and abuse proactively
- Develop systems, tools, and heuristics for rapid detection and scalable enforcement
- Investigate incidents directly in data and build analytics capabilities to establish what happened, size patterns, and distinguish abuse from false positives
- Build monitoring for risk, abuse spikes, and fraud while reducing false positives
- Set technical direction for abuse prevention and define patterns for other engineers
- Work with data scientists on feature exploration and training risk and abuse ML models
Requirements:
- 4+ years building and operating production systems, ideally including trust & safety, fraud, payments risk, security, or anti-abuse experience
- Proficient in React, TypeScript, Next.js, and JavaScript runtimes
- Ability to write SQL against large event datasets
- Ability to reason about base rates, precision and recall, and the cost of a wrong decision
- Sound judgment when working with incomplete evidence
- High agency and a bias toward action
- AI-forward workflow, including frequent use of coding agents and workflow automation
- Comfortable in a small, fast-moving environment with fluid team boundaries
- Discretion and resilience when reviewing or discussing disturbing content and handling sensitive user data
- Strong written and verbal communication
- Motivation by adversarial problems
- Nice to have: payments fraud tooling experience, including Stripe Radar, chargebacks, disputes, or crypto payment risk
- Nice to have: identity and KYC systems experience
- Nice to have: LLM-specific abuse experience, including jailbreaks, prompt injection, key theft and resale, shared or scraped credentials, or automated account farming
- Nice to have: large-scale analytical datastores such as ClickHouse or BigQuery and observability platforms
- Nice to have: familiarity with hosted-AI reporting and compliance obligations
- Nice to have: OpenRouter usage or side projects in AI products, infrastructure, or developer tooling
Benefits:
- Equity
- Remote work in the US
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