The Prospect

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 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

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