ElevenLabs — the world’s leading AI voice research and product company, valued at $11 billion with $781M raised from Andreessen Horowitz, ICONIQ Growth, and Sequoia, serving millions of users and thousands of businesses including Deutsche Telekom and Meta — is seeking an experienced AI Safety Engineer (Free Tier Abuse) to drive the deployment and operationalisation of automated moderation and guardrail systems across ElevenLabs’ multimodal platform. This product ownership role builds production-grade safety infrastructure from the ground up — applying Python, AWS/GCP, Docker, Kubernetes, Prometheus, and Grafana to detect and prevent free-tier abuse, fraud, and bot farming at scale — requiring 6+ years of backend engineering experience with proven free-tier abuse or fraud detection capability.
About ElevenLabs — Transforming Human-Technology Interaction Through AI Voice
Company: ElevenLabs — an AI research and product company that launched in January 2023 with the world’s first human-like AI voice model, now serving millions of users and thousands of enterprise clients globally
Valuation: $11 billion — with $781M in total funding from Andreessen Horowitz, ICONIQ Growth, and Sequoia — one of the fastest and most credibly backed AI companies in history
Platforms: ElevenAgents (voice and chat agent deployment), ElevenCreative (speech, music, image, and video generation across 70+ languages), and ElevenAPI (AI audio foundational model access for developers)
Culture: High-velocity, AI-first, impact-not-titles — lean autonomous teams, minimal bureaucracy, and a global team where talent — not location — determines opportunity
Why This AI Safety Engineer Role Stands Out
$11B Platform at Scale — Real Abuse Problem: ElevenLabs serves millions of users globally across free and paid tiers — free-tier abuse, bot farming, and fake accounts represent a genuine, high-priority threat to platform integrity and commercial sustainability at this scale
Product Ownership from 0→1: End-to-end technical ownership of safety infrastructure — architecture through deployment and monitoring — for a company where AI safety engineering directly protects a product used by Deutsche Telekom and Meta
ML + Backend Bridge Role: A genuinely rare combination — translating ML research models into production-grade safety systems, with full infrastructure ownership across APIs, data pipelines, and observability
World-Class Investors & Colleagues: Work alongside IOI medalists, ex-founders, researchers, and engineers building what the company describes as the best work of their lives — backed by Andreessen Horowitz and Sequoia
Position Overview
This AI Safety Engineer — Free Tier Abuse at ElevenLabs designs and builds scalable backend infrastructure for abuse detection, deploying AI/ML models into production systems, architects robust APIs, data pipelines, and service architectures supporting real-time and batch moderation workflows, implements comprehensive monitoring, alerting, and observability systems including SLIs and SLOs, partners with ML engineers to translate research models into production-ready systems and integrates them across ElevenLabs’ product suite, and drives technical decisions and contributes vision to the safety roadmap — building the next generation of platform guardrails for scale and precision across ElevenLabs’ multimodal AI platform used by millions of users and thousands of enterprise clients worldwide.
Why This Role Matters: As AI Safety Engineer — Free Tier Abuse at ElevenLabs, you build the systems that protect one of the world’s most powerful and widely used AI voice platforms from the actors who would exploit it. When free-tier abuse goes unchecked at ElevenLabs’ scale — bot farms generating synthetic voice content at volume, fake accounts bypassing usage limits to access commercial-grade AI audio generation without payment, coordinated campaigns exploiting trial access to produce content that violates the platform’s terms — the consequences affect platform cost sustainability, model quality, regulatory standing, and the trust of the enterprise clients like Deutsche Telekom and Meta who depend on ElevenLabs’ platform integrity. Your abuse detection infrastructure is not a compliance checkbox — it is the engineering foundation that makes ElevenLabs’ $11B platform commercially sustainable and trustworthy.
Key Responsibilities
Abuse Detection Infrastructure Design & Production ML Deployment
- Design and build scalable backend infrastructure for abuse detection — creating the systems that identify and act on free-tier abuse, fraud, fake accounts, and bot farming across ElevenLabs’ multimodal AI platform at millions-of-users scale
- Deploy AI/ML models into production safety systems — partnering with ML engineers to bridge the gap between research model capability and production-grade, observable, scalable real-world deployment
- Architect robust APIs, data pipelines, and distributed service architectures — supporting both real-time abuse signal detection and batch moderation workflow processing across ElevenLabs’ ElevenAgents, ElevenCreative, and ElevenAPI product suite
- Partner with ML engineers to translate research models into production-ready systems — integrating abuse detection and moderation capabilities across the full ElevenLabs product ecosystem
Observability, SLI/SLO Design & Safety System Monitoring
- Implement comprehensive monitoring, alerting, and observability systems — applying Prometheus, Grafana, and equivalent tooling to ensure ElevenLabs’ safety infrastructure is transparent, debuggable, and actionable at all times
- Establish Service Level Indicators (SLIs), Service Level Objectives (SLOs), and performance benchmarks for all safety systems — creating the measurement framework that drives continuous improvement of abuse detection reliability and precision
- Build observable systems from first principles — ensuring every safety infrastructure component produces the logs, metrics, and traces needed for rapid diagnosis and improvement of abuse detection performance
- Design alerting frameworks that detect safety system degradation proactively — enabling the team to respond to emerging abuse patterns, detection gaps, or infrastructure failures before they have commercial impact
Safety Roadmap Leadership & Platform Guardrail Innovation
- Drive technical decisions and contribute strategic vision to ElevenLabs’ safety roadmap — shaping how the next generation of platform guardrails should be designed for scale, precision, and multimodal coverage across voice, image, and video
- Take products and systems from 0→1 with measurable impact — bringing the ownership mentality and engineering discipline to build safety infrastructure that demonstrably reduces free-tier abuse rates and protects ElevenLabs’ platform integrity
- Collaborate with trust & safety, content moderation, and integrity engineering specialists to design holistic platform protection — ensuring safety systems address the full spectrum of abuse vectors relevant to an AI audio platform at ElevenLabs’ scale
- Contribute to ElevenLabs’ AI-first culture — applying AI tooling to accelerate safety engineering velocity and improve the quality of abuse detection systems throughout the development lifecycle
Requirements
Essential Requirements
- Direct experience tackling free-tier abuse, fraud detection, or fake-account/bot farming at scale — real, demonstrable experience solving this specific class of platform integrity problem is mandatory
- 6+ years of backend software engineering experience building production systems at scale — distributed systems, APIs, data pipelines, and asynchronous Python expertise
- Infrastructure and DevOps proficiency — cloud platforms (AWS or GCP), containerisation (Docker/Kubernetes), and CI/CD pipeline management
- Observability mindset — experience with monitoring tools including Prometheus and Grafana, and a track record of building systems that are inherently observable and debuggable
- Track record of taking products or systems from 0→1 with measurable impact — including deploying or working alongside ML/AI systems in production environments
Bonus Skills
- Trust & Safety, Content Moderation, or Integrity engineering experience
- MLOps experience — deployment, monitoring, and versioning of ML models in production
- Experience with SQL, data analysis tools, real-time streaming systems (Kafka, Redis), or event-driven architectures
- Familiarity with React or modern frontend frameworks
About ElevenLabs — Defining the Future of AI Voice
ElevenLabs launched in January 2023 with the world’s first human-like AI voice model and has grown to an $11 billion company serving millions of users and thousands of enterprises globally — with $781M raised from Andreessen Horowitz, ICONIQ Growth, and Sequoia. Across three platforms — ElevenAgents, ElevenCreative, and ElevenAPI — ElevenLabs is transforming how businesses, creators, and developers interact with AI audio across 70+ languages. The AI Safety Engineer role in UAE represents a chance to join a generational company at one of its most consequential engineering challenges — protecting a platform that is reshaping human-technology interaction, at scale, from abuse that would compromise both its commercial sustainability and its trustworthiness for the enterprise clients who depend on it.
Career Excellence: Build production-grade free-tier abuse detection infrastructure for ElevenLabs’ $11B AI voice platform — Python, AWS, Docker, K8s, fraud detection at scale, remote from UAE.
Who Should Apply?
- Free Tier Abuse & Fraud Detection Engineers: With direct, verifiable experience building abuse detection systems targeting free-tier exploitation, bot farming, fake account creation, or fraud at scale — in a consumer AI, SaaS, or platform product company
- Production Backend Engineers — Python + Cloud: With 6+ years of distributed systems, async Python, API architecture, and cloud (AWS/GCP) experience — building production-grade systems that perform reliably at millions-of-users scale
- MLOps & ML-Integrated Safety Engineers: With experience deploying, monitoring, and versioning ML models in production safety systems — bridging the gap between research-grade model capability and production-grade reliability
- Observability-First Infrastructure Engineers: With Prometheus, Grafana, and SLI/SLO design experience — building safety infrastructure that is transparent, alerting-ready, and continuously improvable through data-driven performance measurement
- Remote UAE-Based AI Safety Professionals: Seeking a high-impact, fully remote safety engineering role at a $11B AI company backed by Andreessen Horowitz and Sequoia — building platform protection infrastructure for a product used by millions of users and Fortune 500 enterprises globally
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