- Employment type
- Full-time · On-site
- Posted
- September 25, 2026
- Salary range
- $90,000–$175,000 CAD per year
- Province
- Quebec (QC)
Hiring confidence: Some gaps · 40/100
Some signals are missing from this posting. It may well be genuine, but it is worth confirming the role is still open before you invest time in applying. How this is scored
Job Overview
This role is based in Quebec. CGI is hiring for this full-time position through Jobily, where you can check how well your resume matches the posting before you apply.
Market context
About this role in Quebec
Average salary for AI Solution Architect in Quebec
Median $70,720 per year, with most postings between $50,000 and $99,409 (Architects, 2026-08, 5 postings). This posting advertises $90,000–$175,000.
NOC code
This posting has not been matched to a NOC 2021 unit group yet. Use the NOC finder to identify the code from the duties listed above.
Typical qualifications for Canadian employers
- Experience designing end-to-end AI and ML solutions
- Knowledge of Large Language Models (LLM) and RAG architectures
- Understanding of AI agents and MLOps pipelines
- Familiarity with cloud platforms and ML frameworks
- Experience with generative AI tools
Fit check
Is this role right for you?
Top skills this posting asks for:
- Artificial Intelligence (AI)
- Machine Learning (ML)
- Large Language Models (LLM)
Jobily reads your resume against this posting and scores the fit — the skills you already have, the gaps, and what to change before applying. Signed-in Premium members see the score at the top of this page.
Scan your resume to see your fitKeep looking
Similar jobs
What you'll do
- Design and architect end-to-end AI and ML solutions aligned with client business needs
- Assess client requirements and propose tailored AI architectures
- Implement solutions including LLMs, RAG systems, and AI agents
- Define and justify technology choices and trade-offs to stakeholders
- Establish MLOps pipelines and practices
- Collaborate with data and software engineering teams
What you'll need
- Experience designing end-to-end AI and ML solutions
- Knowledge of Large Language Models (LLM) and RAG architectures
- Understanding of AI agents and MLOps pipelines
- Familiarity with cloud platforms and ML frameworks
- Experience with generative AI tools
- Ability to assess client needs and propose tailored solutions
- Stakeholder management and communication skills