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 rapid 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 new 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

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