Role: Azure AI Architect
Location: Toronto, ON(Hybrid)
Type: Contract
Rate: CAD80/hr - CAD90/hr
Job Description:
We are seeking a Senior Azure AI Architect to lead the architecture and design of enterprise-scale AI and Generative AI solutions on Microsoft Azure.
The role translates complex business requirements into secure, scalable, resilient, and cost-effective AI architectures, with a focus on Microsoft Foundry, Azure OpenAI, Generative AI, RAG, Agentic AI, Azure AI Search, and enterprise data integration.
The architect serves as a senior technical advisor to business and engineering teams, driving architecture decisions from discovery and PoC through production and operationalization.
Role Boundary
The Azure AI Architect owns architecture, standards, technology direction, security patterns, governance alignment, and target-state solution design. Engineering execution, team delivery management, and release readiness sit with the AI Engineer Lead.
Key Responsibilities
Strategy & Architecture Ownership
- Own the target-state architecture and technology governance for enterprise AI and GenAI solutions on Azure.
- Own AI platform strategy, including model selection, scalability, resiliency, performance optimization, and cost management.
- Ensure alignment with enterprise architecture standards, roadmaps, and principles.
- Define AI architecture principles, reference architectures, reusable patterns, standards, and technology roadmaps.
- Evaluate emerging AI models, frameworks, and Azure capabilities and recommend adoption based on enterprise value.
Solution Design
- Architect solutions using Microsoft Foundry, Azure OpenAI, Azure AI Search, Azure Machine Learning, and Azure AI services.
- Design enterprise-grade RAG architectures, including document ingestion, chunking strategies, embeddings, vector/hybrid search, grounding, citations, and access controls.
- Architect Agentic AI solutions, including multi-agent patterns, tool/function integration, enterprise APIs, knowledge sources, and workflow orchestration.
- Lead LLM/model selection and evaluation based on accuracy, reasoning capability, latency, throughput, security, availability, and cost.
- Architect integration between AI platforms and enterprise applications, databases, APIs, document repositories, data platforms, and event-driven systems.
Platform, Security & Governance
- Establish architectural patterns for prompt management, evaluation, observability, model lifecycle management, LLMOps/MLOps, and AI application monitoring.
- Define security architectures covering Microsoft Entra ID, managed identities, RBAC, Key Vault, private networking, encryption, API security, and sensitive-data protection.
- Establish Responsible AI and AI governance controls covering safety, privacy, explainability, evaluation, hallucination management, and human oversight.
Collaboration & Leadership
- Partner with application, cloud, data, cybersecurity, infrastructure, and enterprise architecture teams.
- Lead architecture workshops, technical discovery sessions, design reviews, PoCs, and stakeholder presentations.
- Provide technical direction and mentorship to AI engineers, ML engineers, application developers, data engineers, and cloud engineers
Experience & Qualifications
- 12+ years of overall technology experience.
- 5+ years in Solution, Cloud, Data, or Application Architecture.
- Strong Azure architecture experience.
- Demonstrated architecture experience with AI/ML and Generative AI.
- Hands-on implementation experience with Azure OpenAI/Foundry and RAG solutions.
- Experience defining enterprise AI roadmaps and leading AI programs from PoC to production at enterprise scale.
- Experience providing architecture leadership across multiple engineering teams.
- Strong experience working directly with customers and senior technology stakeholders.
- Estimation and solution-planning experience.
- Ability to lead and mentor geographically distributed engineering teams.
Key Attributes
- Strong customer-facing and executive communication.
- Ability to translate business problems into AI use cases and architecture.
- Strong critical thinking and problem-solving abilities.
- Ability to lead architecture and solution-design workshops and to articulate alternatives and trade-offs.
- Ability to constructively challenge technical assumptions.
- Strong architecture documentation and presentation skills.
Must-Have Skills
- Microsoft Foundry / Azure OpenAI
Good-to-Have Skills
- Multi-agent architectures
