Closed listing
Principal Agentic AI Architect
- Mississauga, ON, Canada
Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Full-time
- Closing date
- Experience
- 12+ years of software engineering experience, including 5+ years designing and building enterprise AI/ML platforms.
- Posting language
- English
- Posted
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Archived listing. The details below describe a past opening.
Job Title: Principal Agentic AI Architect
Location: MISSISSAUGA, ONTARIO Onsite
Job Type: Full-Time Permanent
Bachelors or Masters degree in Computer Science, Artificial Intelligence, Engineering, or related discipline.
- 12+ years of software engineering experience, including 5+ years designing and building enterprise AI/ML platforms.
- Proven experience architecting and delivering large-scale AI solutions, Agentic AI systems, AI platforms, or multi-agent frameworks in enterprise environments.
- Deep understanding of the Agentic AI ecosystem including agent orchestration, planning, reasoning, tool calling, memory management, retrieval systems, and autonomous workflows.
- Hands-on expertise building AI applications using frameworks and platforms such as Google ADK, LangGraph, LangChain, Semantic Kernel, CrewAI, AutoGen, or similar agentic frameworks.
- Strong experience designing scalable orchestration layers, tool libraries, context management frameworks, observability solutions, and governance controls for AI systems.
- Expertise in Retrieval-Augmented Generation (RAG), vector databases, embeddings, enterprise knowledge systems, and document intelligence platforms.
- Experience designing extensible and reusable AI platform architectures capable of supporting multiple business use cases and domains.
- Strong software engineering background in cloud-native architectures, distributed systems, APIs, microservices, and platform engineering.
- Deep understanding of AI observability, monitoring, evaluation frameworks, model governance, security, and responsible AI principles.
- Exceptional communication and stakeholder management skills with the ability to influence senior technology leaders and architects.Strong understanding of Agile, Waterfall, and Hybrid delivery methodologies.
More about this job
Responsibilities
Architect and deliver scalable enterprise Agentic AI systems, platforms, and multi-agent frameworks, including orchestration, context management, reusable tools, retrieval systems, and autonomous workflows. Establish extensible platform architectures with observability, evaluation, governance, security, and responsible AI controls, while influencing senior technology stakeholders.
Requirements
Requires a bachelor's or master's degree in Computer Science, Artificial Intelligence, Engineering, or a related discipline, plus 12+ years of software engineering experience, including 5+ years designing and building enterprise AI/ML platforms. Candidates should have proven enterprise AI architecture experience, hands-on familiarity with agentic frameworks and RAG, strong cloud-native and distributed-systems expertise, and excellent communication and stakeholder-management skills.
Skills
- Agentic AI Architecture
- Enterprise AI/ML Platforms
- Agent Orchestration
- Planning And Reasoning
- Tool Calling
- Memory Management
- LangGraph
- LangChain
- Retrieval-Augmented Generation
- Vector Databases
- Distributed Systems
- Cloud-Native Architecture
- AI Observability
- Model Governance
- Responsible AI
- Stakeholder Management
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Engineering
- Data & Analytics
- Management & Leadership
Keywords
- Agentic AI
- Google ADK
- LangGraph
- LangChain
- Semantic Kernel
- CrewAI
- AutoGen
- AI/ML Platforms
- Multi-Agent Frameworks
- Agent Orchestration
- Planning
- Reasoning
- Tool Calling
- Memory Management
- Retrieval-Augmented Generation
- Vector Databases
- Embeddings
- Enterprise Knowledge Systems
- Document Intelligence
- Cloud-Native Architecture
- Distributed Systems
- APIs
- Microservices
- Platform Engineering
- AI Observability
- Evaluation Frameworks
- Model Governance
- Responsible AI
- Agile
- Waterfall