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About the Role

AI Engineering transforms emerging AI capabilities and business needs into secure, scalable, production-ready applications and platforms for KPMG Canada. As the Enterprise Architect for AI Engineering, you will provide architectural leadership across our technology portfolio, with a particular emphasis on security, compliance, risk management, and production readiness. You will manage high-level technical architecture, ensure alignment with KPMG enterprise standards, and help establish the controls, patterns, and technology choices that enable secure delivery. You will also serve as a key interface between AI Engineering and KPMG’s broader architecture, security, and technology organizations, coordinating reviews and approvals required to move solutions safely into production.

Responsibilities

Author the architecture of AI Engineering solutions, creating and maintaining high-level architecture documentation and Technical Architecture Documents (TADs) covering application, data, integration, cloud infrastructure, network, identity, security, deployment, and operations.
Ensure new solutions and material changes align with KPMG enterprise architecture, cloud, security, data, and technology standards.
Lead security architecture and production-readiness reviews, identifying required controls, risks, and remediation activities, and coordinating approvals required to move solutions into production.
Govern vulnerabilities and security findings continuously across applications, infrastructure, containers, dependencies, and cloud environments; assess risk, drive remediation, and coordinate mitigating controls, exceptions, or risk acceptance where required.
Review significant application, infrastructure, network, platform, and AI-related changes for architecture, security, and compliance impact.
Establish and evolve reusable architecture patterns, security controls, and guardrails that enable teams to deliver securely and consistently.
Review, select, and govern SDLC tooling used by development teams, including source control, CI/CD, infrastructure-as-code, security scanning, artifact management, and deployment tooling, coordinating enterprise and security approvals where required.
Act as the primary compliance and control reviewer for AI Engineering, maintaining required 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, including identity, least privilege, network security, secrets management, logging, monitoring, and data protection.
Assess security and architecture implications of AI technologies, including models, agents, enterprise data integrations, AI platforms, content-safety controls, and third-party services.
Maintain visibility into key architecture decisions, risks, exceptions, and remediation commitments, and communicate material issues to AI Engineering leadership and relevant enterprise stakeholders.
Monitor developments in cloud, cybersecurity, AI security, enterprise architecture, and regulatory requirements and translate them into practical standards and controls.

Requirements

A 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.
Strong 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, preferably including Azure networking, Entra ID, Key Vault, Application Gateway/WAF, Azure Front Door, Azure Container Apps or Kubernetes, Azure Monitor, Defender for Cloud, and Sentinel.
Strong understanding of modern DevSecOps and SDLC tooling, including source control, CI/CD, infrastructure-as-code, software composition analysis, SAST, container/image scanning, and artifact management.
Experience working with technologies such as GitHub, Terraform, containers, and automated deployment pipelines, with the ability to assess new development tooling from architecture, security, and enterprise-readiness perspectives.
Strong understanding of security and compliance frameworks and control environments, 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 required to demonstrate control effectiveness.
Experience assessing vulnerabilities and security findings, 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, model and service integrations, content safety, and governance.
Ability to translate complex technical and security topics into clear architecture decisions, risks, and recommendations for technical teams and senior stakeholders.
Strong collaboration, organizational, and written communication skills, with the ability to drive architecture, security, and approval activities across multiple enterprise groups.

Skills

AI Engineering
Enterprise Architecture
Security Architecture
Compliance
Risk Management
Production Readiness
Cloud Security
Secure-by-design principles
Identity and Access Management
Least Privilege
Network Security
Encryption
Secrets Management
Logging
Monitoring
Vulnerability Management
Microsoft Azure
Cloud-native architecture
Azure networking
Entra ID
Key Vault
Application Gateway/WAF
Azure Front Door
Azure Container Apps
Kubernetes
Azure Monitor
Defender for Cloud
Sentinel
DevSecOps
SDLC tooling
Source control
CI/CD
Infrastructure-as-code
Software Composition Analysis
SAST
Container/image scanning
Artifact management
GitHub
Terraform
Containers
Automated deployment pipelines
NIST-based controls
ISO standards
Secure SDLC practices
Enterprise technology risk management
Generative AI
Agentic systems

Location

Ontario Region

Work Type

Full-time

Experience Level

Significant experience in enterprise, solution, cloud or security architecture

Education Level

University degree in computer science, engineering, cybersecurity, information systems or a related discipline

Salary/Compensations

$130,000 to $180,000

Benefits

May be eligible for bonus awards
Comprehensive and competitive Total Rewards program

About the Company

At KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges. Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage. Join a firm where your career can make a difference.
Our Values, The KPMG Way: Integrity, we do what is right | Excellence, we never stop learning and improving | Courage, we think and act boldly | Together, we respect each other and draw strength from our differences | For Better, we do what matters
We embrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. AI tools may help with organizing applications or surfacing relevant qualifications. However, no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals, who are equipped with training that empowers them to use these tools responsibly. AI technologies used in our recruitment process undergo detailed risk assessments, including security and privacy requirements, that align with KPMG’s Trusted AI framework.
We believe technology should empower human judgment, not replace it. It’s one of the many ways we’re delivering on our vision of being a technology-first, people-driven firm.

Equal Opportunity

KPMG in Canada is a proud equal opportunities employer and we are committed to creating a respectful, inclusive and barrier-free workplace that allows all of our people to reach their full potential. A diverse workforce is key to our success and we believe in bringing your whole self to work. We welcome all qualified candidates to apply and hope you will choose KPMG in Canada as your employer of choice.
At KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel. We aim to provide a positive experience and are prepared to offer adjustments or accommodations to help you perform at your best. Adjustments (informal requests), such as extra preparation time or the option for micro breaks during interviews, and accommodations (formal requests), such as accessible communication supports or technology aids, are tailored to individual needs and role requirements. You will have an opportunity to request an adjustment or accommodation at any point throughout the recruitment process. If you require support, please contact KPMG’s Employee Relations Service team by calling 1-888-466-4778.