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AI Engineer
Canada Guaranty
Toronto, CAN
Full-time
Mid · 3+ years experience
Hybrid
CAD 115000-135000 yearly / year
Discovered 1 weeks ago
PythonMistralLlama
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Who We Are
Canada Guaranty is a privately held Canadian mortgage insurer, established in 2010 following the acquisition of AIG United Guaranty Mortgage Insurance Company Canada by the Ontario Teachers’ Pension Plan and National Mortgage Guaranty Holdings Inc.
As a proudly Canadian company, we are committed to service excellence and helping Canadians achieve successful, long-term homeownership. Our mortgage solutions help protect lenders and investors from losses related to borrower default and foreclosure while ensuring Canadians are provided with greater access to affordable and sustainable homeownership.
Canada Guaranty’s performance-driven culture thrives on accountability, collaboration, and supportive teamwork. If you’re a dedicated team player with a strong track record of excellence, we can’t wait to hear from you!
About The Opportunity
The AI Engineer is responsible for designing and building AI solutions that deliver measurable business value to Canada Guaranty. The role combines software engineering, machine learning, generative AI, data engineering, and MLOps practices to develop scalable and secure AI applications.
The successful candidate will have hands-on experience developing AI-powered applications and contributing to the lifecycle of AI solutions from experimentation and model selection through deployment, monitoring, and ongoing optimization. While extensive years of AI-specific experience are not required, the candidate must demonstrate practical exposure to production AI environments and a strong understanding of enterprise AI delivery practices.
In this role, you will:
Design and develop AI-powered applications using large language models (LLMs), machine learning models, retrieval-augmented generation (RAG), and related AI technologies.
Develop production-grade AI services, APIs, and integrations using Python and modern software engineering practices.
Provide technical recommendations to business and technology stakeholders on AI capabilities, limitations, risks, and implementation approaches.
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