AI Information Security Engineer
Core
Design, implement, and maintain end-to-end security controls across the AI/ML lifecycle for Large Language Models (LLMs), Small Language Models (SLMs), and open-source models.
Role type
AI Security Engineer (hands-on IC)
Builds
Security guardrails, controls, boundary mechanisms, and AI-driven tooling for cybersecurity posture.
Domain
Cybersecurity, AI/ML security, Cloud security
Deliverable
production ML models
Required skills
AI/ML lifecycle security, adversarial ML, data poisoning, prompt injection, model inversion, model evasion, inference attacks, encryption, masking, tokenization, SSDLC, DevSecOps, SAST, DAST, SCA, threat modeling, application security architecture, Docker, microservices, Python, Go, PyTorch, Hugging Face Transformers, TensorFlow, AWS, Azure, GCP, AI/ML services, application security assessment tools (Burp Suite, ZAP, Tenable WAS)
Preferred skills
AI red teaming, adversarial prompt testing, LLM security assessments, security certifications (CISSP, CSSLP, SANS GIAC, CEH, AI-focused)
Technologies
PyTorch, Hugging Face Transformers, TensorFlow, Burp Suite, ZAP, Tenable WAS, AWS, Azure, GCP
Responsibilities
Design and implement security controls for AI systems; monitor AI landscape for vulnerabilities; develop security reference architectures for AI deployment patterns; deploy controls for model integrity and access; build AI-driven tooling for cybersecurity; perform AI safety and security assessments and threat modeling; collaborate with engineering teams to integrate security best practices; create security guidance and documentation.
Seniority
Mid-level, hands-on IC
