Software Engineer, Trust & Safety

This is a fully remote position, open to applicants in United States.

📋 Description

• Develop and manage systems related to signup, payment processing, and usage to identify abuse and fraud at an early stage.

• Take ownership of the technical enforcement pipeline, overseeing everything from detection to human review and restrictions across various systems.

• Create internal tools for investigation and enforcement, which includes managing case queues, summarizing evidence, enabling bulk reviews and implementations, and issuing investigation alerts.

• Deliver solutions for content safety along the inference path, focusing on illegal-content detection and reporting.

• Construct or incorporate KYC systems and external intelligence sources to proactively identify and prevent fraud and abuse.

• Design systems, tools, and heuristics for swift detection and scalable enforcement measures.

• Directly investigate incidents within data and develop analytics capabilities to understand occurrences, identify patterns, and differentiate abuse from false positives.

• Establish monitoring systems for risk, spikes in abuse, and fraud while minimizing false positives.

• Set the technical strategy for abuse prevention and outline patterns for other engineering teams.

• Collaborate with data scientists on exploring features and training machine learning models related to risk and abuse.

⛳️ Requirements

• A minimum of 4 years of experience in building and operating production systems, preferably with a focus on trust & safety, fraud detection, payment risk, security, or anti-abuse initiatives.

• Expertise in React, TypeScript, Next.js, and JavaScript runtimes.

• Capability to write SQL queries against large event datasets.

• Proficient in analyzing base rates, precision, recall, and the implications of erroneous decisions.

• Sound judgment when dealing with incomplete information.

• High level of agency with a proactive approach to action.

• Familiarity with AI-driven workflows, including regular utilization of coding agents and workflow automation.

• Comfortable working in a small, dynamic environment with fluid team structures.

• Discretion and resilience when reviewing or discussing sensitive content and handling user data.

• Strong written and verbal communication skills.

• Driven by challenges posed by adversarial problems.

• Nice to have: experience with payment fraud tools, such as Stripe Radar, chargebacks, disputes, or risks associated with crypto payments.

• Nice to have: experience with identity verification and KYC systems.

• Nice to have: experience in addressing LLM-specific abuse, including jailbreaks, prompt injections, key theft and resale, shared or scraped credentials, or automated account farming.

• Nice to have: familiarity with large-scale analytical data stores like ClickHouse or BigQuery and observability platforms.

• Nice to have: understanding of hosted AI reporting and compliance requirements.

• Nice to have: experience with OpenRouter or personal projects in AI products, infrastructure, or developer tools.

🏝️ Benefits

• Equity

• Remote work opportunities within the US