AI Engineer

Canada Guaranty•Toronto, ON

7d•CA$115,000 - CA$135,000•Hybrid

About The Position

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 participating in the end-to-end lifecycle of AI solutions, from experimentation and model selection through deployment, monitoring, governance, and ongoing optimization. While significant AI-specific experience are not required, the successful candidate must demonstrate practical exposure to production AI environments and a strong understanding of enterprise AI delivery practices.

Requirements

Bachelor's degree in Computer Science, Software Engineering, Data Science, Engineering, or a related discipline.
At least 3 years of software engineering, machine learning engineering, or AI engineering experience.
Demonstrated involvement in the design and development of AI or machine learning solutions within enterprise environments.
Strong software engineering background with experience developing production-grade applications.
Proficiency in Python and modern AI development frameworks.
Understanding of machine learning lifecycle, MLOps, and related best practices.
Knowledge of AI governance, responsible AI principles, model risk management, privacy, and security considerations.
Strong analytical, troubleshooting, and problem-solving skills.

Nice To Haves

Experience with LLM platforms such as OpenAI, Mistral, Llama, or similar models.
Familiarity with vector databases, embeddings, semantic search, and knowledge retrieval architectures.
Experience contributing to AI governance, model review, or risk management processes.

Responsibilities

Design and develop AI-powered solutions using large language models (LLMs), machine learning models, prompt engineering, model orchestration, and related AI technologies.
Evaluate and integrate commercial, open-source, and proprietary AI models.
Design and develop production-grade AI services and APIs.
Implement AI applications using Python and modern software engineering practices.
Build reusable AI components, frameworks, and libraries to accelerate delivery.
Apply secure coding practices and ensure maintainability, scalability, and reliability of AI solutions.
Collaborate with data engineers and business teams to identify, prepare, and curate training and retrieval datasets.
Develop and maintain vector databases, embeddings, feature stores, and model pipelines.
Evaluate model accuracy, explainability, performance, and operational suitability.
Conduct model benchmarking and performance testing.
Ensure AI solutions comply with organizational AI governance, security, privacy, and regulatory requirements.
Participate in AI risk assessments, model validation, and approval processes.
Maintain documentation supporting model decisions, limitations, assumptions, and controls.