Principal AI Security Researcher

Job not on LinkedIn

🔥 0 minutes ago

🇮🇱 Israel – Remote

⏰ Full Time

🔴 Lead

👮‍♂️ Cybersecurity / Security Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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ActiveFence

WebsiteLinkedInAll Job Openings

201 - 500 employees

🔒 Cybersecurity

🤖 Artificial Intelligence

💰 $400M Series B on 2021-07

Cybersecurity • Artificial Intelligence

ActiveFence is a Trust and Safety provider for online platforms, protecting platforms and their users from malicious behavior and content. Trust and Safety teams of all sizes rely on ActiveFence to keep their users safe from the widest spectrum of online harms, unwanted content, and malicious behavior, including child safety and exploitation, disinformation, hate speech, terror, nudity, fraud, and more. We offer a full stack of capabilities with our deep intelligence research, AI-driven harmful content detection, and online content moderation platform. Protecting over three billion users globally everyday in over 100 languages, ActiveFence lets people interact and thrive online.

📋 Description

• Lead and scale multidisciplinary teams focused on AI red teaming, adversarial testing, and AI security research. • Design and execute sophisticated attacks against LLMs, GenAI applications, and agentic AI systems. • Research prompt injection, jailbreaks, indirect prompt injection, tool abuse, agent manipulation, data leakage, model misuse, and adversarial behavior. • Build and evolve AI red-teaming engines and automated adversarial testing systems, including RLGym. • Build and scale global AI security teams across red teaming, adversarial research, and guardrails engineering while fostering an innovation-driven security culture. • Oversee advanced adversarial evaluations for GenAI models, agentic AI, and multi-agent (A2A) systems. • Define and implement AI red-teaming frameworks aligned with OWASP AI Security guidelines, MITRE ATLAS, and NIST AI RMF. • Operationalize automated red-team engines to continuously stress-test models at scale. • Partner with product and engineering to design and deploy enterprise-ready AI guardrails, including policy enforcement layers, monitoring pipelines, and anomaly detection systems. • Champion secure GenAI deployment practices, including agent orchestration via MCP and A2A workflows.

🎯 Requirements

• Extensive leadership experience managing and scaling security or R&D organizations, with a strong track record of building high-performance teams and driving complex projects to completion. • Deep expertise in cybersecurity and AI, including AI threats, adversarial machine learning, LLM vulnerabilities, and AI safety frameworks such as OWASP Top 10 for LLMs and NIST AI Risk Management Framework. • Strategic mindset and execution skills, with the ability to set vision and direction for AI security initiatives and dive into technical details when needed. • Excellent communication and collaboration abilities, including cross-functional work with product, engineering, and compliance teams and conveying technical concepts to executive stakeholders. • 5+ years of relevant industry experience in cybersecurity, machine learning security, or related fields, focused on enterprise-scale products and AI systems. • Demonstrated thought leadership in AI security, such as publishing research, speaking at industry events, or contributing to AI security standards and open-source projects. • Experience building or deploying AI security products and tools, including red teaming automation platforms, guardrail frameworks, or AI monitoring and anomaly detection systems. • Hands-on familiarity with agentic AI frameworks and protocols such as LangChain, AutoGen, MCP, and A2A, and cloud-based AI environments. • Background in AI trust and safety or adversarial ML research, with insight into emerging threats and mitigation techniques for GenAI applications.