Senior Security Engineer - AI Focus

Euna Solutions; Oakville; On-site; CAD 120,000 - 180,000; Full time

Job summary

Euna Solutions in Oakville, Ontario, is seeking a seasoned Security Engineer with hands-on AI/ML security experience. This role focuses on securing AI/ML development lifecycles, implementing security automation, and driving governance across teams.

You will collaborate with Architecture, Product Development, Platform, DevOps, and IT to embed robust security controls, assess risks, and deliver end-to-end security for AI-enabled systems.

Qualifications

• Minimum 7-10 years in hands-on security architecture and engineering in a SaaS org.
• Experience driving cross-functional security initiatives in an agile SaaS environment.
• Solid foundation in AppSec core domains.
• Hands-on security architecture and implementation in microservice, cloud-native, and serverless contexts.
• Familiar with AI/ML security risks and governance frameworks (OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, EU AI Act).

Responsibilities

• Assess and mitigate AI/ML security risks including model integrity and prompt injections.
• Implement and maintain security tooling and automation across AI/ML pipelines.
• Define secure AI development practices across the SDLC.
• Evaluate secure agentic AI systems and multi-agent architectures.
• Contribute to AI governance initiatives and risk assessments.
• Embed AI security controls across engineering and operations teams.
• Own AI security projects end-to-end from conception to delivery.
• Develop and maintain technical security documentation for AI systems.
• Support compliance initiatives, audits, and technical assessments.

Skills

Security architecture

Cloud-native

GitOps

Security automation

AI/ML security

Tools

LangChain

AutoGen

CrewAI

Job description

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 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