Senior Security Engineer - AI Focus

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Security Engineer - AI Focus based in Canada.

This is a senior security engineering opportunity for an experienced professional looking to apply deep cybersecurity expertise to the rapidly evolving world of AI and machine learning.
You will help secure AI/ML systems, infrastructure, development pipelines, and emerging agentic architectures against sophisticated and evolving threats.
The role combines hands-on security engineering, automation, architecture, compliance, and AI governance across the development lifecycle.
You will work closely with Architecture, Product Development, Platform, Dev Ops, and IT teams to embed security into how AI-enabled products are designed and delivered.
The position offers significant ownership, from identifying emerging risks and designing controls to implementing solutions and driving projects through completion.
You will also contribute to responsible AI practices and help establish security standards for technologies that are changing rapidly.
This is a fully remote position in Canada, with preference for candidates working in the Eastern Time Zone.

• Assess, identify, and mitigate security risks associated with AI/ML systems, including model integrity, data poisoning, prompt injection, adversarial attacks, and emerging agentic AI threats.
• Design, implement, and maintain security processes, tooling, and automation across AI/ML development pipelines and supporting infrastructure.
• Define and enforce secure AI development and delivery practices throughout the software development lifecycle.
• Evaluate and secure agentic AI environments, including autonomous agents, multi-agent architectures, tool-use frameworks, orchestration layers, memory systems, and autonomous decision‑making workflows.
• Apply established security engineering principles across cloud‑native, microservice, serverless, and modern application architectures.
• Champion continuous security and compliance practices across AI/ML environments and development operations.
• Contribute to AI governance initiatives, including security policies, risk assessments, responsible AI frameworks, and controls aligned with regulatory and industry standards.
• Partner with engineering, architecture, product, platform, Dev Ops, and IT stakeholders to embed effective AI security controls into existing workflows.
• Lead AI security initiatives and projects from initial concept and risk assessment through implementation, delivery, and ongoing improvement.
• Develop and maintain clear technical documentation covering AI systems, models, architectures, security controls, and operational practices.
• Support security compliance activities, audits, technical assessments, and incident response efforts relevant to AI/ML environments.
• Identify opportunities to strengthen security automation and use AI‑enabled approaches to improve security engineering effectiveness.

• 7–10+ years of hands‑on experience in security architecture and engineering within an agile SaaS or software development environment.
• Proven experience leading cross‑functional security initiatives and influencing engineering teams toward stronger security practices.
• Strong foundation in application security (App Sec), security architecture, cloud security, and modern software development practices.
• Hands‑on experience securing microservice, cloud‑native, and serverless application architectures.
• Strong experience with Git Ops implementation, security, and operational use.
• Demonstrated ability to develop security tooling and automation as software.
• Experience implementing continuous security and compliance practices across development environments.
• Recent hands‑on exposure to securing AI/ML environments and understanding of their unique security challenges.
• Working knowledge of AI/ML security frameworks and standards such as OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF, and the EU AI Act
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• Understanding of agentic AI architectures and associated risks, including autonomous agents, tool orchestration, memory systems, and multi‑agent…