Position: Principal Agentic AI Architect
Location: Mississauga, ON (Hybrid)
Employment Type: Full-Time
Experience Required: 12 + Years
Position Overview:
We are seeking an experienced Principal AI Platform Architect to lead the design and delivery of enterprise-scale Agentic AI and AI Platform solutions. The ideal candidate will have deep expertise in AI/ML architectures, multi-agent systems, RAG frameworks, cloud-native platforms, and enterprise software engineering.
Key Responsibilities:
- Define and drive the enterprise AI platform and Agentic AI architecture strategy.
- Design scalable AI frameworks enabling multiple business use cases across the organization.
- Lead development of multi-agent ecosystems, RAG solutions, and intelligent automation platforms.
- Establish AI governance, observability, security, and operational best practices.
- Collaborate with business and technology leaders to identify and implement AI-driven innovations.
- Mentor engineering teams and provide architectural leadership on AI initiatives.
Required Skills:
- Bachelor's or master's degree in computer science, Artificial Intelligence, Engineering, or a related field.
- 12+ years of software engineering experience, including 5+ years building enterprise AI/ML platforms.
- Proven experience designing and delivering Agentic AI solutions, AI platforms, multi-agent systems, and autonomous workflows.
- Strong knowledge of agent orchestration, planning, reasoning, memory management, tool calling, retrieval systems, and AI governance.
- Hands-on experience with frameworks such as LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, Google ADK, or similar.
- Expertise in RAG architectures, vector databases, embeddings, enterprise knowledge management, and document intelligence solutions.
- Experience building scalable AI orchestration platforms, reusable components, observability frameworks, and governance controls.
- Strong background in cloud-native architectures, distributed systems, microservices, APIs, and platform engineering.
- Solid understanding of AI monitoring, evaluation frameworks, security, compliance, and Responsible AI principles.
- Excellent stakeholder management, communication, and leadership skills.
- Experience working within Agile, Waterfall, and Hybrid delivery models.
