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Agentic AI Architect - Intelligence Engineering (Toronto)
Slalom
CAN
Full-time
Senior
Hybrid
CAD 123,000 to CAD 163,000 per year
Discovered 2 weeks ago
Agentic AI architectureMulti-agent systemsGenerative AILarge language modelsRetrieval-augmented generationPython
Free
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Agentic AI architectureMulti-agent systemsGenerative AI
Role Overview
Design and deliver innovative AI/ML and agentic AI solutions that automate or re-envision human workflows on AWS, Azure, and Google Cloud.
Help clients move from isolated proofs of concept to secure, scalable, observable systems with measurable business value.
Key Skills for This Role
Agentic AI architectureMulti-agent systemsGenerative AILarge language modelsRetrieval-augmented generationPython
Full Job Posting
Mission
Design and deliver innovative AI/ML and agentic AI solutions that automate or re-envision human workflows on AWS, Azure, and Google Cloud.
Help clients move from isolated proofs of concept to secure, scalable, observable systems with measurable business value.
What you’ll do
- Provide thought leadership on AI/ML, generative AI, and agentic AI internally and with clients.
- Design end-to-end agentic architectures, including planning loops, memory management, tool integration, and agent coordination.
- Architect multi-agent orchestration systems using frameworks such as LangGraph, Strands Agents SDK, OpenAI Agents SDK, or Google ADK.
- Design Model Context Protocol server integrations for enterprise tool use, data access, and interoperability.
- Build advanced RAG systems using vector databases, embeddings, hybrid search, re-ranking, and multi-source synthesis.
- Build Python-based ML systems, APIs, evaluation harnesses, retrieval pipelines, agent workflows, and production services.
- Implement CI/CD, testing, deployment, observability, evaluation, safety guardrails, and AI governance frameworks.
- Explain system behavior to technical and non-technical audiences through presentations, workshops, and architecture discussions.
- Collaborate with Product Owners to initiate, deliver, and transition client-facing projects.
- Lead and mentor engineers and ML practitioners, including technical leadership of smaller 3–5 person projects.
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