Senior AI Developer / Generative AI Engineer

Location: Toronto, ON (Hybrid – 3 days onsite per week)

Required Skills & Qualifications

• Strong hands-on expertise in Python and SQL, with experience in software engineering and developing production-ready AI applications and enterprise solutions.
• Extensive experience developing Generative AI (GenAI) applications, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI solutions.
• Strong hands-on experience with Microsoft Azure AI Foundry (Microsoft Foundry), Azure Machine Learning (Azure ML), Azure OpenAI, and Azure AI Services for enterprise AI solution development.
• Proven experience designing and developing AI Agents, intelligent automation solutions, reusable AI components, APIs, and AI-powered enterprise applications.
• Strong understanding of LLM architecture, Prompt Engineering, Context Engineering, Model Evaluation, and AI performance optimization.
• Experience building and implementing RAG pipelines, including integrating LLMs with enterprise data sources, knowledge bases, APIs, and business applications.
• Strong technical foundation in Machine Learning and Statistics, including Classification, Regression, Clustering, Feature Engineering, Model Training, Model Evaluation, and ML Pipelines.
• Experience developing and integrating REST APIs, enterprise applications, data platforms, and automated business workflows using AI-powered solutions.
• Hands-on experience with Databricks, Power Automate, VS Code, Git, and JIRA, supporting AI development, data integration, workflow automation, and software delivery.
• Strong understanding of Software Engineering Best Practices, including version control, testing, CI/CD, technical documentation, deployment, monitoring, and performance optimization.
• Experience developing secure, scalable, and production-ready AI solutions while incorporating Responsible AI, AI Governance, Data Privacy, Security, and Data Protection principles.
• Ability to collaborate with Data Scientists, Data Engineers, Data Architects, Product Managers, and Business Stakeholders to translate business requirements into practical AI solutions.

Additional Asset: Previous experience delivering enterprise AI solutions or digital transformation initiatives within public sector organizations.