AI Security Engineer

Euna Solutions•Dunwoody, GA

3d•Hybrid

About The Position

We’re looking for a seasoned Security Engineer who has started applying that expertise to AI/ML systems. This role is a natural next step for someone who knows the security fundamentals inside and out and is now getting hands-on with the unique threat landscape that comes with AI — prompt injection, model integrity, agentic pipelines, and the rest. You don’t need to have spent years in a dedicated AI security role; what matters is that you’ve got the security depth and the curiosity to learn fast in a space that’s evolving quickly. Working under the Director of Security Engineering & Operations, you’ll drive security implementation, automation, and compliance across our AI/ML development lifecycle — collaborating closely with Architecture, Product Development, Platform, DevOps, and IT.

Requirements

Minimum 7-10 years of experience in a hands-on security architecture and engineering role in an agile SaaS development organization
Proven success driving cross-functional security initiatives in an agile SaaS development organization
Solid foundation and experience in AppSec core domains
Direct, hands-on, end to end, experience with the following: Security architecture and implementation in context of microservice, cloud-native, and serverless application architectures
GitOps implementation, security, and utilization
Security tooling and automation development, as software
Continuous security and compliance
Recent hands-on exposure to securing AI/ML environments
Working familiarity with AI/ML security risks and frameworks — OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act. You don’t need to have lived in these for years; you need to understand what they’re solving for
Awareness of agentic AI architectures and the risks that come with them — autonomous agents, tool orchestration, memory systems, multi-agent coordination

Nice To Haves

Direct experience with LLM security, model red-teaming, or AI threat modeling
Hands-on work securing agentic AI systems (e.g., LangChain, AutoGen, CrewAI, or similar frameworks)
Experience contributing to or implementing AI governance programs, risk registers, or responsible AI policies
Experience with security incident response in AI/ML environments
Familiarity with AI governance principles: model transparency, explainability, bias/fairness considerations, and data lineage
Relevant certifications, e.g. ISC2 (AI Security, CISSP, CCSP, CSSLP, ISAAP, ISSEP)

Responsibilities

Assess and mitigate security risks specific to AI/ML systems — including model integrity, data poisoning, prompt injection, adversarial attacks, and agentic AI threat vectors
Implement and maintain security processes, tooling, and automation across AI/ML pipelines and infrastructure
Define and enforce secure AI development and delivery practices across the SDLC
Evaluate and help secure agentic AI systems, including multi-agent architectures, tool-use frameworks, and autonomous decision-making pipelines
Contribute to AI governance initiatives, including policy development, risk assessments, and responsible AI frameworks aligned with regulatory and industry standards
Partner cross-functionally to embed AI security controls across engineering and operations teams
Own AI security projects end-to-end, from conception through delivery
Develop and maintain technical security documentation for AI systems and models
Support compliance initiatives, audits, and technical assessments relevant to AI/ML environments