Harden login and registration flows using risk-based controls such as rate limiting, behavioral signals, progressive friction, and automated mitigation.
Partner closely with Security and Engineering teams to identify and remediate abuse.
Develop internal Trust & Safety tooling that centralizes risk signals, improves investigation workflows, and automates enforcement actions.
Create and productionize abuse detection logic by translating adversarial patterns into scalable signals, metrics, and engineering controls.

Requirements

BA/BS degree or equivalent experience
5–8 years of software engineering experience, with at least 2–3 years in trust & safety, security engineering, or fraud/abuse prevention
Proficiency in one or more backend languages (Python, Go, Node.js, etc.)
Experience building and maintaining internal tooling at scale
Experience building and publishing applications on cloud platforms (AWS, Cloudflare, etc.)
Familiarity with data pipelines and querying large datasets (SQL, BigQuery, etc.) to surface abuse patterns
Experience with rate limiting, fingerprinting, bot detection, or similar abuse prevention primitives
Experience implementing observability, metrics, and alerting (OpenSearch, Datadog, CloudWatch, etc.)

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonGoNode.jsSQLBigQueryrate limitingfingerprintingbot detectionobservabilitymetrics

Certifications

BA/BS degree