8 дней назад
Software Engineer (Trust & Safety)
215 000 - 285 000$
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Software Engineer (Trust & Safety) (AI infrastructure): Building detection, enforcement, review, and monitoring systems that protect an AI routing platform from abuse, fraud, malicious users, and illegal content with an accent on inference-path safety, payments risk, and large-scale event analysis. Focus on designing adaptive abuse-prevention systems, reducing false positives, building reviewer tooling, and collaborating on risk and abuse ML models.
Location: Remote (US)
Salary: $215,000–$285,000 per year, plus equity.
Company
provides an AI routing and infrastructure layer for enterprises to access, manage, and optimize large language models across providers.
What you will do
- 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.
- Develop case queues, evidence summaries, bulk review tools, alerting, and investigation workflows.
- Implement content-safety systems for the inference path, including illegal-content detection and reporting.
- Investigate incidents in large datasets, build risk monitoring, and reduce false positives.
- Set technical direction for abuse prevention and collaborate on risk and abuse ML models.
Requirements
- 4+ years 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.
- Sound judgment with incomplete evidence, strong communication, and a bias toward action.
- Comfort working in a small, fast-moving environment with fluid team boundaries.
- Discretion and resilience when reviewing disturbing content and handling sensitive user data.
Nice to have
- Experience with Stripe Radar, chargebacks, disputes, crypto payment risk, identity, or KYC systems.
- Experience with LLM abuse patterns such as jailbreaks, prompt injection, key theft, credential scraping, or account farming.
- Experience with ClickHouse, BigQuery, observability platforms, hosted-AI compliance, or illegal-content reporting.
- usage or side projects in AI products, infrastructure, or developer tooling.
Culture & Benefits
- Full-time remote work from the US.
- Hands-on individual-contributor role with broad ownership and a direct path to shipping.
- Work on evolving adversarial problems where threat models and abuse patterns change quickly.
- Compensation includes equity.
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