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