Solutions Architect (Enterprise AI)

Montréal, Québec

On-site

Full-time

No salary posted2 days ago

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Employment type: Full-time · On-site
Posted: September 14, 2026
Province: Quebec (QC)

Hiring confidence: Sparse posting · 22/100

This posting is missing most of the signals we look for, or shows patterns common to listings that are not actively being filled. Check with the employer before applying. How this is scored

Job Overview

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Job Description Job Description ABOUT THE COMPANY Our client is a deep-tech intelligence ecosystem building technology that enables organizations to understand, decide and act across complex real-world environments. At the foundation of the ecosystem is a dedicated research capability that develops advanced technologies across multimodal intelligence, world models, temporal systems, signal processing and other emerging fields. These capabilities are productized through our client’s core AI orch…

This role is based in Quebec. Flatgigs 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 Solutions Architect (Enterprise AI) in Quebec

Median $93,600 per year, with most postings between $93,600 and $93,600 (Architects, 2026-05, 1 postings). This posting does not state a salary.

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

Enterprise AI architecture experience
Deep technical knowledge of AI/ML systems
Experience with multimodal intelligence systems
Cloud platform expertise
Client-facing experience

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What you'll do

Design enterprise AI solutions for complex real-world environments
Architect systems leveraging multimodal intelligence and world models
Translate client requirements into technical solutions
Guide productization of advanced AI capabilities
Collaborate with research and engineering teams
Lead technical discussions with enterprise clients

What you'll need

Enterprise AI architecture experience
Deep technical knowledge of AI/ML systems
Experience with multimodal intelligence systems
Cloud platform expertise
Client-facing experience
Advanced understanding of temporal systems and signal processing