AI Information Security Engineer

tenableinc

United States

On-site

USD 120,000 - 190,000

Full time

4 days ago
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Job summary

Tenable is seeking an AI Security Engineer to join the Information Security team. You will design and implement security controls across the AI/ML lifecycle, define guardrails for LLMs and other AI models, and help secure Tenable’s products and enterprise AI initiatives.

You will collaborate with software, product, and security teams to embed best practices into AI development, training, validation, and deployment.

Qualifications

  • 2+ years of professional experience in information security or application security.
  • Awareness of AI-specific security threats (adversarial ML, data poisoning, prompt injection).
  • Knowledge of SSDLC/DevSecOps and security testing (SAST, DAST, SCA, threat modeling).
  • Experience with modern web app architectures, Docker, and microservices.

Responsibilities

  • Design, implement, and maintain end-to-end security controls across the AI/ML lifecycle.
  • Develop security guardrails for LLMs/SLMs and open-source models.
  • Monitor AI security threats and apply engineering expertise to defend deployments.
  • Create security guidance, documentation, and training for engineers.

Skills

AI security
Threat modelling
Security testing
Cross-functional collaboration
Communication
Independent work

Education

Bachelor's degree

Tools

Docker
PyTorch
TensorFlow
Transformers
SAST

Job description

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!

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 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 time building or tinkering 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.
  • Assist in the implementation of robust security guardrails, controls, and boundary mechanisms for Large Language Models (LLMs), Small Language Models (SLMs), and open-source models.
  • Continuously monitor the AI landscape for novel vulnerabilities and attack techniques, applying deep engineering experience to proactively defend enterprise AI deployments.
  • Assist in developing 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.
  • Create security guidance, documentation, and training for internal engineering and development teams; develop metrics that drive desired security behaviors and outcomes.
  • Assist in researching emerging trends in AI security and contribute to innovative solutions that support Tenable's AI initiatives.
What You'll Need:
  • 2 or more years of professional experience in information security or application security, with at least a demonstrated interest on securing AI/ML systems.
  • Bachelor's Degree in Computer Science, Cybersecurity, Data Science, or a related field preferred.
  • Awareness of AI-specific security threats, including adversarial ML, data poisoning, prompt injection, model inversion, model evasion, and inference attacks.
  • Knowledge of data security principles, including encryption, masking, and tokenization.
  • Knowledge of SSDLC, DevSecOps, and security testing practices, including SAST, DAST, SCA, and threat modeling.
  • Knowledge of application security architecture best practices and patterns, including modern web applications, Docker, and microservices.
  • Ability to work cross-functionally across engineering, product, and business teams.
  • Strong written and verbal communication skills; able to clearly translate complex AI security risks for both technical and non-technical audiences.
  • Strong problem-solving skills, attention to detail, and ability to lead projects with end-to-end ownership.
  • Self-motivated and effective working independently and across distributed teams.
And Ideally:
  • Hands-on experience with AI red teaming, adversarial prompt testing, or LLM security assessments.
  • Basic coding experience in Python and/or Go.
  • Experience with frameworks & libraries such as PyTorch, Hugging Face Transformers, TensorFlow or similar.
  • Strong understanding of the ML/AI lifecycle and the security risks associated with each stage.
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