Software Engineer, Trust & Safety
New
R
ResendEmail software
Location: Europe; This role is fully remote based in Americas or European timezones, Americas or European timezonesFull-TimeSenior
Salary150,000 - 175,000 USD per year
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Job Details
- Languages
- Fluent in writing and speaking English
- Experience
- 5+ years of software engineering experience
- Required Skills
- AWSNode.jsTypeScriptGoPostgresRedisReactDatadog
Requirements
- Bring 5+ years of software engineering experience.
- Be fluent in writing and speaking English.
- Have deep experience with Node.js, TypeScript, and React; Hono and Next.js are also listed.
- Write Go or be willing to use it for latency-sensitive services.
- Have infrastructure and reliability skills, including AWS, CDK, and Datadog.
- Be comfortable with APIs, event-driven architectures, queues, and stateful services.
- Design systems that fail safe and treat false positives as bugs.
- Have observability experience with metrics, logs, tracing, and error handling.
- Take ownership across frontend surfaces, databases, and queues.
- Have proven experience with Postgres and Redis.
- Trust and safety, fraud, or security experience is an exceptional-fit qualification.
- Experience with real-time enforcement, rate limiting, or rules engines such as CEL is an exceptional-fit qualification.
- Production experience with ML- or LLM-based detection and measuring precision and recall is an exceptional-fit qualification.
- Email knowledge, including SPF, DKIM, DMARC, bounces, complaints, and phishing campaigns, is an exceptional-fit qualification.
- Database performance tuning with Postgres or Redis is an exceptional-fit qualification.
Responsibilities
- Build and run the real-time enforcement layer within a millisecond latency budget.
- Design pipelines that move from signal to decision to action across sending, receiving, and account activity.
- Build detection rules and policies, and make them safe to change.
- Detect and contain account takeovers and leaked API keys.
- Measure detection precision using reasons recorded for blocks and reversals, and retire detections that harm good senders.
- Automate investigations, appeals, and bulk actions.
- Build and evaluate ML classifiers for spam and phishing, and measure their precision before enforcement.
- Implement safeguards and make enforcement actions traceable through logs, metrics, and audit trails.
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