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Senior AI Information Security Engineer

Tenable USAUSD 122,500–163,167 / yearSenior

Key requirements

  • Python
  • Go
  • Aws
  • Azure
  • Gcp
  • Docker
  • Ci/Cd
  • Llm
  • Data Science
  • Risk Management
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 percent of the Fortune 500, 50 percent of the Global 2000, and large government agencies. Come be part of our journey! What makes Tenable such a great place to work? Ask a member of our team and they’ll answer, “Our people!” We work together to build and innovate best-in-class cybersecurity solutions for our customers; all while creating a culture of belonging, respect, and excellence where we can be our best selves. When you’re part of our #OneTenable team, you can expect to partner with some of the most talented and passionate people in the industry, and have the support and resources you need to do work that truly matters. We deliver results that exceed expectations and we win together! Applicants must be authorized to work for any employer in the U.S. without sponsorship. We are unable to provide sponsorship for work visas of any kind at the time of hire, or at any point during employment. This includes, but is not limited to: 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, and you will be on the front lines of defining how we assess, test, and address it. You will apply hands-on AI engineering experience alongside deep product security and application security skills to design security controls for AI systems, lead assessments, and help engineering teams ship AI features securely. You will establish security standards for responsible AI use, influence decisions across the organization, and build tooling that raises our security posture. This role is ideal for a practitioner who has spent real time building with AI systems, looking under the hood of model internals, and wants to channel that experience into a security specialty. Your Opportunity: Design, implement, and maintain end-to-end security controls across the AI/ML lifecycle. Conduct safety research, inspecting model internals (e.g., detecting hidden deception, latent knowledge, or unwanted concepts across layers) as a core methodology. Perform AI safety assessments and threat modeling for AI/ML systems, identifying risks such as data poisoning, model evasion, model extraction, adversarial inputs, and integrity attacks. Design and implement robust security guardrails, controls, and boundary mechanisms for Large Language Models (LLMs), Small Language Models (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, ensuring highly transparent and aligned AI outputs. Continuously monitor the AI landscape for novel vulnerabilities and attack techniques, applying deep engineering experience to proactively defend enterprise AI deployments. Develop security reference architectures for AI deployment patterns, including MCP servers and agentic AI workflows and 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. Perform AI safety, security assessments, threat modeling for AI/ML systems, identifying risks such as data poisoning, model evasion, model extraction, adversarial inputs, and integrity attacks. Collaborate with software engineers, and product teams to integrate security best practices into AI development, training, validation, and deployment processes. Drive Secure Software Dev

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