Principal AI Solution Architect (Toronto)

Principal AI Solution Architect (Toronto)

10 Aug
|
S.i. Systems
|
Toronto

10 Aug

S.i. Systems

Toronto

Our client is building a new AI Centre of Excellence (AI COE) to accelerate the adoption of Artificial Intelligence across the organization. The Centre of Excellence is focused on three strategic pillars:

- Generative AI
- Robotic Process Automation (RPA)
- Data Science

As part of this initiative, we are seeking a Principal AI Solution Architect to lead the design and implementation of an enterprise-scale Generative AI platform that will serve as the foundation for AI innovation across the organization.

This is a highly technical, hands-on architecture role for someone who has successfully built enterprise AI platforms—not just AI applications—and can translate architecture into production-ready solutions.

The Opportunity

As the Principal AI Solution Architect, you will be responsible for defining and delivering the organization's enterprise GenAI platform. Your work will enable development teams to rapidly build secure, governed, and reusable AI solutions by providing common frameworks, services, and architectural patterns that can be leveraged across multiple business domains.

You will work closely with engineering teams to move AI capabilities from concept and prototype through production, ensuring the platform is scalable, secure, observable, and continuously improving.

This is not a strategy-only architecture position. The successful candidate will remain technically hands-on, building proofs of concept, developing reusable components, and partnering closely with engineers throughout delivery.

Key Responsibilities

- Design and architect an enterprise-wide Generative AI platform from the ground up.
- Develop reusable AI capabilities, frameworks, SDKs, libraries, and reference architectures that support multiple business use cases.
- Establish scalable architectural patterns for enterprise AI adoption.
- Lead the technical design of Agentic AI and multi-agent architectures.
- Design secure, governed, and production-ready AI solutions aligned with enterprise standards.
- Partner with engineering teams to implement architecture and operationalize AI solutions into production.
- Build prototypes and proof-of-concepts to validate architectural decisions.
- Define GenAIOps best practices, including CI/CD pipelines, deployment automation, monitoring, and continuous evaluation.
- Collaborate with cross-functional teams to establish governance, security, observability, and responsible AI practices.
- Mentor senior engineers and provide technical leadership across the AI Centre of Excellence.
- Drive continuous improvement of the enterprise AI platform as recent technologies and business needs emerge.

Required Qualifications

- Extensive experience designing and implementing enterprise-scale AI or Generative AI platforms.
- Demonstrated success building reusable AI platforms supporting multiple production use cases.
- Proven experience taking AI solutions from prototype through enterprise production deployment.
- Strong hands-on software engineering background with the ability to prototype and contribute code when required.
- Experience defining enterprise architecture standards, reusable frameworks, and platform services.
- Strong understanding of AI governance, security, scalability, observability, and operational excellence.




- Experience collaborating closely with engineering teams throughout implementation and delivery.

Required Technical Expertise

Data & Platform Technologies

- Databricks

AI Engineering & Operations

- GenAIOps
- CI/CD pipelines for AI applications
- Monitoring and evaluation of GenAI systems
- AI observability
- Prompt and model lifecycle management
- Agentic AI architectures
- Multi-agent systems
- Reusable AI services and frameworks
- Production AI infrastructure

Nice-to-Have Experience

- Agent Identity
- Financial services or other highly regulated industry experience
- Experience establishing enterprise AI governance frameworks

What We're Looking For

The ideal candidate has already built an enterprise AI platform—not simply delivered AI applications.

They will be able to clearly demonstrate experience with:

- Designing enterprise-wide AI platforms from the ground up.
- Creating reusable AI capabilities used across multiple teams.
- Building modular and extensible AI architectures.
- Implementing robust governance and security controls.
- Operationalizing AI solutions for enterprise production.
- Establishing monitoring, evaluation, and continuous improvement practices.
- Working closely with engineers to turn architectural designs into production-ready solutions.

Overview

Our client is building a new AI Centre of Excellence (AI COE) to accelerate the adoption of Artificial Intelligence across the organization. The Centre of Excellence is focused on three strategic pillars:

- Generative AI
- Robotic Process Automation (RPA)
- Data Science

As part of this initiative, we are seeking a Principal AI Solution Architect to lead the design and implementation of an enterprise-scale Generative AI platform that will serve as the foundation for AI innovation across the organization.

This is a highly technical, hands-on architecture role for someone who has successfully built enterprise AI platforms—not just AI applications—and can translate architecture into production-ready solutions.

The Opportunity

As the Principal AI Solution Architect, you will be responsible for defining and delivering the organization's enterprise GenAI platform. Your work will enable development teams to rapidly build secure, governed, and reusable AI solutions by providing common frameworks, services, and architectural patterns that can be leveraged across multiple business domains.

You will work closely with engineering teams to move AI capabilities from concept and prototype through production, ensuring the platform is scalable, secure, observable, and continuously improving.

This is not a strategy-only architecture position. The successful candidate will remain technically hands-on, building proofs of concept, developing reusable components, and partnering closely with engineers throughout delivery.

Key Responsibilities

- Design and architect an enterprise-wide Generative AI platform from the ground up.




- Develop reusable AI capabilities, frameworks, SDKs, libraries, and reference architectures that support multiple business use cases.
- Establish scalable architectural patterns for enterprise AI adoption.
- Lead the technical design of Agentic AI and multi-agent architectures.
- Design secure, governed, and production-ready AI solutions aligned with enterprise standards.
- Partner with engineering teams to implement architecture and operationalize AI solutions into production.
- Build prototypes and proof-of-concepts to validate architectural decisions.
- Define GenAIOps best practices, including CI/CD pipelines, deployment automation, monitoring, and continuous evaluation.
- Collaborate with cross-functional teams to establish governance, security, observability, and responsible AI practices.
- Mentor senior engineers and provide technical leadership across the AI Centre of Excellence.
- Drive continuous improvement of the enterprise AI platform as new technologies and business needs emerge.

Required Qualifications

- Extensive experience designing and implementing enterprise-scale AI or Generative AI platforms.
- Demonstrated success building reusable AI platforms supporting multiple production use cases.
- Proven experience taking AI solutions from prototype through enterprise production deployment.
- Strong hands-on software engineering background with the ability to prototype and contribute code when required.
- Experience defining enterprise architecture standards, reusable frameworks, and platform services.
- Strong understanding of AI governance, security, scalability, observability, and operational excellence.
- Experience collaborating closely with engineering teams throughout implementation and delivery.

Required Technical Expertise

Microsoft Azure AI Ecosystem

- Azure AI Foundry
- Azure AI Services
- Azure OpenAI
- Azure AI Search
- Azure Document Intelligence
- Azure Identity

Data & Platform Technologies

- Azure Data Lake Storage (ADLS)
- Cosmos DB
- Azure SQL
- Databricks

AI Engineering & Operations

- GenAIOps
- CI/CD pipelines for AI applications
- Production AI deployment
- Monitoring and evaluation of GenAI systems
- AI observability
- Prompt and model lifecycle management

AI Architecture

- Agentic AI architectures
- Multi-agent systems
- Enterprise AI platform design
- Reusable AI services and frameworks
- Production AI infrastructure

Nice-to-Have Experience

- Microsoft Copilot Studio
- Agent Identity
- Model Context Protocol (MCP)
- Financial services or other highly regulated industry experience
- Experience establishing enterprise AI governance frameworks

What We're Looking For

The ideal candidate has already built an enterprise AI platform—not simply delivered AI applications.

They will be able to clearly demonstrate experience with:

- Designing enterprise-wide AI platforms from the ground up.
- Creating reusable AI capabilities used across multiple teams.
- Building modular and extensible AI architectures.
- Implementing robust governance and security controls.
- Operationalizing AI solutions for enterprise production.
- Establishing monitoring, evaluation, and continuous improvement practices.
- Working closely with engineers to turn architectural designs into production-ready solutions.

📌 Principal AI Solution Architect (Toronto)
🏢 S.i. Systems
📍 Toronto

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