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AI/ML Architecturefreelance.ca • Toronto, Canada
AI/ML Architecture

AI/ML Architecture

freelance.ca • Toronto, Canada
30+ days ago
Job type
  • Full-time
Job description
Role: AI/ML architecture
Location: Toronto, ON
Duration: Long Term Contract

Job Description:

The ideal candidate will have strong expertise in AI/ML architecture, LLM ecosystems, automation frameworks, enterprise integration, and responsible AI principles, with the ability to translate business use cases into scalable AI-enabled solutions.
Key Responsibilities
1. Agentic AI Architecture & Strategy
Define the target-state architecture for agentic AI platforms and solutions across enterprise use cases
Design frameworks for multi-agent orchestration, reasoning workflows, memory, tool usage, and decision loops
Establish reusable architecture patterns for autonomous and semi-autonomous AI agents
Drive alignment between business priorities, AI capabilities, and enterprise architecture standards
2. Solution Design & Integration
Architect AI agent solutions integrated with:
Enterprise applications
Workflow automation platforms
Knowledge management systems
APIs, databases, and collaboration platforms
Design scalable, modular, and resilient integration patterns for AI agents operating across hybrid environments
Enable interoperability between LLMs, vector stores, orchestration layers, and enterprise systems
3. Governance, Risk & Responsible AI
Establish guardrails for responsible AI adoption, including transparency, explainability, fairness, and accountability
Define governance controls for:
Agent permissions
Decision approval workflows
Human-in-the-loop oversight
Data access and usage boundaries
Ensure AI agent design aligns with security, privacy, legal, and compliance requirements
4. Platform Engineering & Operationalization
Work with engineering teams to operationalize AI agent frameworks using modern tooling and platforms
Drive architecture for:
Prompt orchestration
Agent memory and context handling
Model routing and optimization
Monitoring, observability, and performance tuning
Establish deployment patterns for production-grade AI ecosystems
5. Stakeholder Leadership
Partner with business, product, engineering, data, and security teams to identify and prioritize high-value AI use cases
Act as a subject matter expert for agentic AI architecture decisions, standards, and roadmaps
Provide executive-level guidance on AI-enabled transformation opportunities
Required Qualifications
10+ years of experience in solution architecture, enterprise architecture, AI/ML, or emerging technology roles
Strong expertise in:
Generative AI / LLM ecosystems
Agentic AI frameworks and orchestration models
API-led enterprise architecture
Cloud-native platforms (Azure, AWS, GCP)
Experience designing and integrating AI solutions into enterprise environments
Deep understanding of:
AI workflow orchestration
Knowledge retrieval / RAG architectures
Automation and decisioning platforms
Ability to translate complex business requirements into scalable technical architecture
Preferred Qualifications
Experience with:
LLMOps / MLOps / AIOps
Multi-agent systems
Workflow automation platforms
Enterprise integration architecture
Familiarity with regulatory expectations around AI governance, privacy, and risk management
Experience in highly regulated industries such as banking, insurance, healthcare, or public sector
Preferred Certifications
Azure AI Engineer / AWS Machine Learning / Google Professional ML Engineer
TOGAF / SABSA
CISSP / CISM (nice to have)
Relevant AI governance or cloud certifications
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AI/ML Architecture • Toronto, Canada

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