2 months ago
Toronto, CanadaSenior
Responsibilities
- Define enterprise AI security architecture, guardrails, and secure reference architectures for AI platforms, models, and data pipelines.
- Design controls addressing model abuse, data poisoning, adversarial attacks, and other AI-specific threats.
- Architect AI governance, risk classification, impact assessment, control baselines, auditability, explainability, transparency, and accountability frameworks.
- Design secure MLOps pipelines and cloud AI controls for access, identity, secrets management, logging, and third-party or open-source AI models.
- Define data protection architecture, including anonymization, encryption, privacy, and data governance mechanisms.
- Advise executives and boards on AI security and trust, and mentor analysts and AI engineering teams.
Requirements
- Deep understanding of AI and machine learning architectures and lifecycles.
- Strong knowledge of AI security threats and mitigations.
- Expertise in cloud AI platforms and secure cloud architecture.
- Strong background in cybersecurity architecture and risk management.
- Familiarity with AI governance and ethical AI frameworks.
- CISSP, ISO 27001 Lead Implementer, NIST AI RMF Practitioner, CCSP, or AI governance and ethics certifications are assets.
Benefits
- Remote work arrangement.
- Full-time, permanent employment.
- Four weeks of cumulative vacation starting from day one.
- Flexible working hours and personal days.
- Professional Development Allowance for training, computer equipment, and physical activities.
- Training tailored to areas of expertise.
- RRSP with employer contributions of up to 3% of gross salary.
- Modular group insurance plan, 11 statutory holidays, and public transportation or parking reimbursement when required.
- Referral bonuses and social activities including 5to7 events, a social club, healthy snacks, and coffee.
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