Remote Ai-security-privacy Jobs in Canada

Requirements

• Bachelor’s or Master’s degree in Computer Science, Cybersecurity related field or equivalent certifications along with work experience.
• 3+ years of experience in application security, cloud security, or platform security engineering.
• Hands-on experience securing distributed systems or cloud-native applications (Kubernetes, APIs, microservices).
• Experience designing and implementing authentication, authorization, and data protection controls.
• Strong programming/scripting skills (Python, Go, or similar) for building security tooling and automation.

Benefits

• 401k Matching
• Certification Support
• Flexible Hours
• Gym Membership
• Health Insurance
• Home Office Budget
• Learning Budget
• Paid Time Off

Skills

Requirements

• 5+ years of software development experience
• Experience independently designing and developing medium to large projects
• Experience working collaboratively across multiple engineering teams
• Ability to drive clear next steps when working in an ambiguous environment
• Ability to think creatively and reason clearly in a complex problem domain
• Experience developing, deploying, and maintaining reliable infrastructure systems
• Experience building security frameworks integrated with core AI infrastructure
• Experience designing and implementing defenses against AI specific threats

Benefits

• 401k Matching
• Certification Support
• Flexible Hours
• Health Insurance
• Home Office Budget
• Learning Budget
• Paid Time Off
• Stock Options

Skills

Requirements

• Lead enterprise-wide initiatives to continuously identify, assess, and remediate vulnerabilities across AI/ML systems
• Oversee the development and execution of vulnerability scanning, penetration testing, and red-teaming exercises specific to AI technologies
• Architect and enforce comprehensive AI security governance structures that align with Responsible AI guidelines, regulatory mandates, and organizational risk appetite
• Develop policies, standards, and approval processes that ensure full lifecycle oversight of AI/ML systems, supporting auditability, transparency, and accountability in all AI operations
• Direct identification, evaluation, and mitigation of risks inherent to AI/ML deployments
• Lead risk assessments, threat modeling, and scenario analysis to anticipate potential weaknesses and prioritize mitigation strategies
• Spearhead proactive threat intelligence, detection, and response to emerging AI threats

Benefits

• 401k Matching
• Certification Support
• Flexible Hours
• Health Insurance
• Home Office Budget
• Learning Budget
• Paid Time Off
• Remote Work

Skills