Software Engineer, Trust & Safety

Compensation

$215K – $285K • Offers Equity

About OpenRouter

OpenRouter is the leading AI routing and infrastructure layer that enterprises use to access, manage, and optimize the best large language models across providers,without lock-in, capacity constraints, or unnecessary cost.

About the Role

We're hiring a Software Engineer on our Trust & Safety team to own the detection, enforcement, and review systems that keep abuse, fraud, malicious users and illegal content off the platform.

You will be responsible for proactive abuse-prevention architecture for a new layer of the AI stack while the abuse patterns are still being invented.

What You'll Do

• Build and operate technical systems across signup, payments, and usage to detect abuse and fraud early.
• Own the technical enforcement pipeline end to end, from detection proposing a candidate to a human reviewing it to restrictions landing across our systems.
• Build the internal tools that support investigation and enforcement decision-making.
• Ship technical solutions for content safety on the inference path: illegal content detection and reporting.
• Help make abuse uneconomical by building systems, tools, and heuristics for quick detection and scalable enforcement.
• Help investigate incidents directly in the data and build the analytics plane.
• Build defensible monitoring for risk, abuse spikes, and fraud, all while reducing false positives.
• Set the technical direction for how we prevent abuse as the platform grows and evolves.
• Work with data scientists on feature exploration and training of risk and abuse ML models.

What We're Looking For

• 4+ years building and operating production systems, ideally including work in trust & safety, fraud, payments risk, security, or anti-abuse.
• Proficient in React, TypeScript, Next.js, and JS runtimes.
• Ability to write SQL against large event datasets and 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 in your workflow, using coding agents often.
• Comfortable in a small, fast-moving environment.
• Discretion and resilience.
• Strong written and verbal communication.
• Motivated by adversarial problems.

Nice to Haves

• Experience with payments fraud tooling.
• Experience with LLM-specific abuse.
• Experience operating large scale analytical datastores.
• Familiarity with the reporting and compliance obligations that come with hosted AI.