Engineering Manager, Agentic AI & Machine Learning
- Employment type
- Full-time · On-site
- Posted
- November 9, 2026
- Province
- Ontario (ON)
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
This role is based in Ontario. Loblaw 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 Ontario
Average salary for Engineering Manager, Agentic AI & Machine Learning in Ontario
Median $130,000 per year, with most postings between $95,000 and $170,000 (Engineering managers, 2026-05, 13 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
- Proven engineering management experience
- Strong background in Machine Learning or AI systems
- Leadership and team management skills
- Experience with technical architecture and design
- Ability to work collaboratively across functions
Fit check
Is this role right for you?
Top skills this posting asks for:
- Engineering Management
- Machine Learning
- AI/Agentic AI
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What you'll do
- Lead engineering teams in Agentic AI and Machine Learning initiatives
- Shape the future of Canadian retail through technology innovation
- Drive strategic technical decisions and architectural planning
- Foster collaboration and commitment within teams
- Positively impact Loblaw's technological capabilities
- Support organizational goals aligned with helping Canadians live life well
What you'll need
- Proven engineering management experience
- Strong background in Machine Learning or AI systems
- Leadership and team management skills
- Experience with technical architecture and design
- Ability to work collaboratively across functions