Software Engineer, Trust & Safety

OpenRouter

. Build and operate systems across signup, payments, and usage to detect abuse and fraud early .

Posted 9/21/2026full-timeRemote • United StatesMid-LevelSenior💰 $215,000 - $285,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and operating systems for fraud detection and abuse prevention, with a strong focus on technical enforcement and analytics capabilities. Proficient in modern programming languages and frameworks, with a solid understanding of risk management and KYC systems.

Highest-signal resume keywords

ReactTypeScriptNext.jsSQLFraud Detection

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Fraud PreventionPayments RiskData AnalysisMachine LearningHeuristic Development

Soft Skills

Strong CommunicationSound JudgmentHigh AgencyResilienceMotivation by Adversarial Problems

Tools & Technologies

Stripe RadarClickHouseBigQueryKYC SystemsAI Workflow Automation

Industry Keywords

Trust & SafetyAbuse PreventionContent SafetyRisk ManagementIdentity Verification

Tech Stack

Tools & technologies

BigQueryJavaScriptNext.jsReactSQLTypeScript

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

Equity
Remote work in the US