Application Deadline:10/29/2026Address:33 Dundas Street WestJob Family Group:Technology#AIJobsBFUTRAbout the RoleWe are seeking an innovative AI Engineer to help drive the next generation of intelligent solutions across the enterprise. In this role, you will design, develop, deploy, and optimize AI-powered applications, machine learning solutions, and intelligent automation capabilities that deliver measurable business value. You will partner closely with business stakeholders, data scientists, engineers, and technology leaders to identify opportunities where artificial intelligence can enhance customer experiences, improve operational efficiency, reduce risk, and accelerate decision-making.
The successful candidate combines strong software engineering expertise with practical experience in machine learning, generative AI, automation, and cloud technologies. You are passionate about transforming complex business challenges into scalable AI solutions and thrive in a quick-paced, collaborative environment.

Key Responsibilities
AI Solution DevelopmentDesign, build, deploy, and maintain AI and machine learning solutions that address business priorities.
Develop and implement Generative AI, Natural Language Processing (NLP), predictive analytics, and intelligent automation use cases.
Build scalable AI applications, APIs, and services using up-to-date software engineering practices.
Develop proof-of-concepts (POCs), prototypes, and pilot solutions to demonstrate business value and technical feasibility.
Integrate AI models into enterprise systems and workflows.
Machine Learning & Generative AIDevelop, train, evaluate, and optimize machine learning models.
Build and refine Retrieval-Augmented Generation (RAG) solutions, agent-based systems, and LLM-powered applications.
Fine-tune and evaluate AI models to improve performance, reliability,



and business outcomes.
Collaborate with Data Science teams to operationalize models and deploy them into production environments.
Monitor model performance and implement ongoing improvements.
Business Partnership & Innovatio nPartner with stakeholders to understand business challenges and identify AI opportunities.
Translate business requirements into technical designs and implementation plans.
Facilitate workshops, discovery sessions, and solution design discussions.
Create business cases and recommendations for AI investments and initiatives.
Stay current on emerging AI technologies, tools, and industry trends.
Engineering Excellenc eDevelop high-quality, secure, and maintainable code using enterprise standards.
Implement MLOps and DevOps practices to streamline model deployment and lifecycle management.
Establish monitoring, testing, governance, and performance frameworks for AI solutions.
Collaborate with infrastructure and security teams to ensure scalable and compliant deployments.
Contribute to best practices, standards, and reusable AI frameworks.
Project DeliveryParticipate in Agile delivery environments and contribute to sprint planning, backlog refinement, and execution.
Manage project timelines, risks, dependencies, and technical deliverables.
Communicate project status, challenges, and recommendations to technical and business stakeholders.
Support production deployments and ongoing operational sustainability.




Required Qualifications3-5+ years of experience in AI Engineering, Machine Learning Engineering, Software Engineering, or a related field.
Bachelor's degree in Computer Science, Engineering, Data Science, Information Technology, Mathematics, or a related discipline.
Hands-on experience developing machine learning and AI solutions in enterprise environments.
Proficiency in Python and AI/ML frameworks such as TensorFlow, PyTorch, LangChain, Hugging Face, or similar technologies.
Experience building and deploying Generative AI and Large Language Model (LLM) solutions.
Strong understanding of machine learning lifecycle management and MLOps practices.
Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
Experience with API development, data integration, and software engineering best practices.
Knowledge of AI governance, security, risk management, and responsible AI principles.
Experience working in Agile delivery teams.
PreferredExperience with Azure OpenAI, Copilot technologies, AI Agents, or Retrieval-Augmented Generation (RAG) architectures.
Experience implementing intelligent automation, process automation, or workflow orchestration solutions.
Familiarity with vector databases, knowledge management platforms, and semantic search technologies.
Experience in financial services, banking, or other highly regulated industries.
Relevant certifications in AI, cloud computing, or machine learning.
Skills & CompetenciesStrong analytical and problem-solving abilities.
Excellent verbal and written communication skills.
Ability to influence and collaborate with technical and non-technical stakeholders.
Strong execution and project delivery skills.
Data-driven decision making.
Curiosity, adaptability

📌 AI Engineer (Toronto)
🏢 BMO
📍 Toronto