Safety Engineer - Free Tier Abuse
Build production-grade backend infrastructure for detecting free-tier abuse and deploying automated AI safety systems. The role requires 6+ years of backend engineering experience, strong Python and distributed-systems expertise, cloud and observability proficiency, and experience with fraud or bot-abuse prevention.
About the job
Responsibilities
- Design and build scalable backend infrastructure for abuse detection, deploying AI/ML models into production systems.
- Architect robust APIs, data pipelines, and service architectures supporting real-time and batch moderation workflows.
- Implement comprehensive monitoring, alerting, and observability systems; establish SLIs, SLOs, and performance benchmarks.
- Partner with ML engineers to translate research models into production-ready systems and integrate them across the product suite.
- Drive technical decisions and contribute to the safety roadmap for building platform guardrails at scale and with precision.
Requirements
- Direct experience tackling free-tier abuse, fraud detection, or fake-account/bot farming at scale.
- 6+ years of backend software engineering experience building production systems at scale.
- Strong production backend experience with distributed systems, APIs, data pipelines, and Python, including asynchronous Python and backend frameworks.
- Infrastructure and DevOps proficiency with cloud platforms such as AWS or GCP, containerization with Docker and Kubernetes, and CI/CD pipelines.
- Experience with monitoring tools such as Prometheus and Grafana and building observable systems.
- Track record of taking products or systems from 0 to 1 with measurable impact, including deploying or working alongside ML/AI systems in production.
Nice-to-haves
- Trust & Safety, Content Moderation, or Integrity engineering experience.
- MLOps experience, including deployment, monitoring, and versioning of ML models.
- Experience with SQL, data analysis tools, real-time streaming systems such as Kafka and Redis, or event-driven architectures.
- Familiarity with React or modern frontend frameworks.
Compensation and Benefits
- Annual discretionary professional development stipend.
- Annual discretionary social travel stipend.
- Annual company offsite.
- Monthly co-working stipend for employees not near a main hub.
Skills
Python, AWS, GCP, Docker, Kubernetes, CI/CD, Prometheus, Grafana, SQL, Kafka, Redis, React, MLOps, Distributed Systems, Data Pipelines
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