AI Security Engineer - Secure AI at Scale (Remote/Hybrid)

Tenable; Boston (MA); Hybrid; USD 150,000 - 230,000; Full time

Benefits offered by this job

Health insurance

Hybrid or remote opportunities

Professional development and tuition

Job summary

Tenable is seeking an AI Security Engineer to advance security for Tenable's AI-enabled products and enterprise deployments. You will design controls across the AI/ML lifecycle, conduct safety assessments, and build tooling to raise security posture.

The role requires deep expertise in AI security risks, model internals, and secure software practices, with collaboration across engineering and product teams.

Qualifications

• 5+ years of information security or application security experience with at least 1–2 years in securing AI/ML systems.
• Experience inspecting AI model internals and safety risks (adversarial inputs, data poisoning)
• Strong understanding of ML/AI lifecycle security risks and mitigations
• Hands-on with AI red teaming, adversarial prompt testing, or LLM security assessments
• Familiarity with OWASP LLM Top 10 and NIST AI RMF guidance

Responsibilities

• Design, implement, and maintain end-to-end security controls across the AI/ML lifecycle
• Perform AI safety assessments and threat modeling for AI/ML systems
• Develop security reference architectures for AI deployment patterns
• Deploy controls to ensure model integrity, governance, and access control across models and feature stores
• Collaborate with engineers and product teams to embed security into AI development and deployment
• Drive SSDLC and DevSecOps practices for AI-powered products, including threat modeling and security testing

Skills

AI security

Threat modeling

SSDLC

DevSecOps

Python

Go

Security architecture

Communication

Education

Master's degree in Computer Science, Cybersecurity, Data Science, or related field

Tools

PyTorch

Hugging Face Transformers

TensorFlow

Job description

Tenable is seeking an AI Security Engineer to advance security for Tenable's AI-enabled products and enterprise deployments. You will design controls across the AI/ML lifecycle, conduct safety assessments, and build tooling to raise security posture.

The role requires deep expertise in AI security risks, model internals, and secure software practices, with collaboration across engineering and product teams.