AI Security Engineer working at Euna Solutions to assess and mitigate AI/ML-specific security risks. Define and enforce secure AI practices across development cycles while collaborating with engineering teams.
Responsibilities
Assess and mitigate AI/ML-specific security risks
Implement and maintain security tooling, automation, and processes across AI/ML pipelines and infrastructure
Define and enforce secure AI development practices across the full SDLC
Evaluate and secure agentic AI systems
Contribute to AI governance initiatives
Embed AI security controls cross-functionally across engineering and operations teams
Own AI security projects end-to-end, from conception through delivery
Requirements
5–8 years in security engineering, DevSecOps, or a related discipline
Solid foundation across multiple security domains: application security, cloud security, network security, and/or DevSecOps
Working familiarity with AI/ML security frameworks — OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act
Awareness of agentic AI architectures and the risks they introduce
Proficiency in Python and at least one additional scripting language (Ruby or Shell)
Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP)
Direct experience with LLM security, model red-teaming, or AI threat modeling (Nice-to-Have)
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