The Opportunity 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. What You’ll Do - 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 What You’ll Bring Required - 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 Preferred We know AI security is a recent discipline. These aren’t screens — they’re signals of someone who’s been leaning into this space.

- 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 - with AI/ML workloads - Familiarity with AI governance principles: model transparency, explainability, bias/fairness considerations, and data lineage - Relevant certifications, e. g. ISC2 (AI Security, CISSP, CCSP, CSSLP, ISSAP, ISSEP) Location: This position will be remote with preference given to EST time zone. AI Mindset at Euna Solutions We believe the future of work is human + AI.

📌 Senior Security Engineer - AI Focus (Canada)
🏢 Euna Solutions
📍 Canada