Job Description

Toast is recruiting on behalf of one of the largest professional services firms in Canada, a global audit, tax and advisory organization with more than 10,000 people across the country. Their AI Engineering team turns emerging AI capabilities into secure, scalable, production-ready applications and platforms used across the firm. As Enterprise Architect, AI Engineering (Security and Compliance), you will lead architecture across the team’s technology portfolio with a focus on security, compliance, risk and production readiness. You will be the key link between AI Engineering and the firm’s broader architecture, security and technology groups, guiding solutions safely into production. This is a full-time role based in Toronto.

Responsibilities

- Author and maintain high-level architecture documentation and Technical Architecture Documents covering application, data, integration, cloud infrastructure, network, identity, security, deployment and operations
- Ensure new solutions and material changes align with enterprise architecture, cloud, security, data and technology standards
- Lead security architecture and production-readiness reviews, identifying required controls, risks and remediation, and coordinating approvals to move solutions into production
- Govern vulnerabilities and security findings across applications, infrastructure, containers, dependencies and cloud environments, driving remediation and coordinating mitigating controls, exceptions or risk acceptance
- Review significant application, infrastructure, network, platform and AI-related changes for architecture, security and compliance impact
- Build and evolve reusable architecture patterns,



security controls and guardrails so teams can deliver securely and consistently
- Review, select and govern SDLC tooling, including source control, CI/CD, infrastructure-as-code, security scanning, artifact management and deployment tooling
- Act as the primary compliance and control reviewer for AI Engineering, maintaining evidence and supporting internal reviews, external assessments, certifications and audits
- Partner with engineering, DevOps/SRE, platform and product teams to embed secure-by-design practices across identity, least privilege, network security, secrets management, logging, monitoring and data protection
- Assess the security and architecture implications of AI technologies, including models, agents, enterprise data integrations, AI platforms, content-safety controls and third-party services
- Track key architecture decisions, risks, exceptions and remediation commitments, and communicate material issues to AI Engineering leadership and enterprise stakeholders
- Stay current on cloud, cybersecurity, AI security, enterprise architecture and regulatory developments and translate them into practical standards and controls

Requirements

- University degree in computer science, engineering, cybersecurity, information systems or a related discipline
- Significant experience in enterprise, solution, cloud or security architecture within complex enterprise environments




- Strong experience designing and reviewing production-grade cloud applications and platforms across applications, APIs, data, infrastructure, identity, networking, security and operations
- Deep knowledge of cloud security and secure-by-design principles, including identity and access management, least privilege, network security, encryption, secrets management, logging, monitoring and vulnerability management
- Experience with Microsoft Azure and cloud-native architecture; hands-on experience with Azure networking, Entra ID, Key Vault, Application Gateway/WAF, Azure Front Door, Azure Container Apps or Kubernetes, Azure Monitor, Defender for Cloud and Sentinel would be a plus
- Strong understanding of modern DevSecOps and SDLC tooling, including source control, CI/CD, infrastructure-as-code, software composition analysis, SAST, container and image scanning and artifact management
- Experience with GitHub, Terraform, containers and automated deployment pipelines, plus the ability to assess current tooling for architecture, security and enterprise readiness
- Strong understanding of security and compliance frameworks such as NIST-based controls, ISO standards, secure SDLC practices and enterprise technology risk management
- Experience supporting architecture, cybersecurity, risk, compliance and audit reviews and producing the documentation and evidence that demonstrates control effectiveness
- Experience assessing vulnerabilities, determining risk, identifying mitigating controls and working through risk-acceptance and exception processes
- Familiarity with security considerations for generative AI and agentic systems, including enterprise data access, identity, mode

📌 Enterprise Architect, AI Engineering – Security (Toronto)
🏢 Toast
📍 Toronto