AI Security Engineer
Tenable · US - Hybrid - Massachusetts - Boston , US - Headquarters - Maryland - Columbia
About this role
**Who is Tenable?** Tenable® is the Exposure Management company. Over 40,000 organizations around the globe rely on Tenable to understand and reduce cyber risk. Our global employees support 65% of the Fortune 500, 50% of the Global 2000, and large government agencies. **What makes Tenable such a great place to work?** We work together to build and innovate best-in-class cybersecurity solutions—while creating a culture of belonging, respect, and excellence. When you’re part of our #OneTenable team, you can expect to partner with talented and passionate people and have the support and resources you need to do work that truly matters. --- ## Applicants must be authorized to work in the U.S. Applicants must be authorized to work for any employer in the U.S. without sponsorship. Tenable is unable to provide sponsorship for work visas of any kind at the time of hire, or at any point during employment (including F1-OPT, F1-CPT, H-1B, TN, J-1, etc.). --- ## Your Role As an **AI Security Engineer** on Tenable’s Information Security team, you will help shape and mature our approach to securing AI—both within Tenable’s products and across the enterprise. AI introduces a new class of risk at the intersection of application security, cloud risk, and data governance. You’ll be on the front lines of defining how we assess, test, and address it. You’ll apply hands-on AI engineering experience alongside deep product security and application security skills to: - Design security controls for AI systems - Lead assessments - Help engineering teams ship AI features securely You will also establish security standards for responsible AI use, influence decisions across the organization, and build tooling that raises our security posture. --- ## Your Opportunity - Design, implement, and maintain end-to-end security controls across the AI/ML lifecycle - Conduct safety research by inspecting model internals (e.g., detecting hidden deception, latent knowledge, or unwanted concepts across layers) - Perform AI safety assessments and threat modeling (e.g., data poisoning, model evasion, model extraction, adversarial inputs, integrity attacks) - Design and implement security guardrails, controls, and boundary mechanisms for LLMs, SLMs, and open-source models - Act as a subject matter expert in AI safety research by inspecting model internals to detect hidden deception, latent knowledge, or unwanted concepts - Continuously monitor the AI landscape for novel vulnerabilities and attack techniques to proactively defend enterprise AI deployments - Develop security reference architectures for AI deployment patterns, including MCP servers and agentic AI workflows/harnesses - Deploy controls to ensure model integrity, governance, and proper access control across models and feature stores - Build AI-driven tooling to strengthen cybersecurity posture across identity, incident management, vulnerability management, third-party risk, and emerging AI threat vectors - Collaborate with software engineers and product teams to integrate security best practices into AI development, training, validation, and deployment - Drive Secure Software Development Lifecycle (SSDLC) and DevSecOps practices for AI-powered products (threat modeling, security testing, penetration testing, CI/CD security automation) - Create security guidance, documentation, and training; develop metrics that drive desired security behaviors and outcomes - Research emerging trends in AI security and cont
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