FREE ACCESS
5,000–10,000 jobs/day
See all jobs on Scoutfield
Search thousands of fresh jobs every day.
Discover
- Fresh listings
- Fast filters
- No subscription required
Create a free account and start exploring right away.

Safety Engineer – Back-End Leaning
ElevenLabs. Design, develop, and scale automated moderation systems, abuse detection capabilities, and guardrails for AI agents across ElevenLabs’ products .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in backend engineering, including API design, distributed systems, and cloud-based applications, while effectively collaborating with cross-functional teams to implement safety policies and scalable engineering solutions. Proficient in deploying and integrating ML models into production systems and building trust and safety infrastructure for AI applications.
Highest-signal resume keywords
Backend EngineeringAPI DesignPython ProficiencyTrust & Safety SystemsML Model Integration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Backend EngineeringAPI DesignPythonDistributed SystemsCloud-Based ApplicationsReal-Time Data ProcessingEvent-Driven ArchitecturesMonitoring ToolsObservability ToolsFrontend Development
Soft Skills
Problem-SolvingCollaboration
Tools & Technologies
KubernetesDockerCI/CD PipelinesAWSGCPPrometheusGrafanaReactKafkaRedis
Industry Keywords
Content ModerationAbuse PreventionSafety InfrastructureAI AgentsLLM-Based Applications
Tech Stack
Tools & technologiesAWSCloudDistributed SystemsDockerGoogle Cloud PlatformGrafanaKafkaKubernetesPrometheusPythonReactRedis
About the role
Key responsibilities & impact- Design, develop, and scale automated moderation systems, abuse detection capabilities, and guardrails for AI agents across ElevenLabs’ products
- Partner with the Investigations team to identify emerging abuse patterns and evolving threats
- Continuously improve safety systems, detection mechanisms, and guardrails to address new risks
- Build and maintain internal safety services, owning architecture, deployment, reliability, monitoring, and ongoing operation
- Deploy and integrate fine-tuned and proprietary ML models into production safety systems
- Develop backend services, APIs, internal tools, and user-facing interfaces for moderation, safety operations, and policy enforcement
- Collaborate with Product, Legal, and Safety Policy teams to translate business, regulatory, and policy requirements into scalable engineering solutions
- Balance product growth, user experience, and platform safety
- Translate legal and regulatory requirements into practical safety systems
- Help implement safety policies technically and inform policy decisions through engineering expertise
- Contribute to architectural decisions and define the evolution of safety infrastructure
Requirements
What you’ll need- 5+ years of software engineering experience building and operating production systems
- Strong backend engineering experience, including designing APIs, working with databases, and building scalable services
- Proficiency in Python and experience with modern backend frameworks
- Experience building and maintaining distributed systems and cloud-based applications
- Comfortable owning systems end to end, from technical design and implementation through deployment, monitoring, and ongoing maintenance
- Experience working across different parts of the stack, with the ability to build internal tools or frontend interfaces when needed
- Strong problem-solving skills and ability to navigate ambiguous requirements and make pragmatic engineering decisions
- Ability to collaborate effectively with engineers and non-technical stakeholders across different functions
- Experience building Trust & Safety, content moderation, fraud detection, or abuse prevention systems
- Experience building guardrails or safety infrastructure for AI agents and LLM-based applications
- Experience deploying and integrating ML models into production applications
- Familiarity with Kubernetes, Docker, CI/CD pipelines, and AWS/GCP
- Experience with monitoring and observability tools such as Prometheus and Grafana
- Experience with React or other modern frontend frameworks
- Experience with real-time data processing, event-driven architectures, Kafka, and Redis
Benefits
Comp & perks- Annual discretionary professional development stipend
- Annual discretionary stipend to meet up with colleagues each year
- Annual company offsite
- Monthly co-working stipend for employees not located near a main hub
- Option to work from ElevenLabs offices in London, New York, San Francisco, and Warsaw