CloudAI Platform Engineer

Location: Toronto ON (Hybrid)
Job Type: Full-Time
Experience Level: New Graduate / Entry Level

Are you looking to make your mark in AI Are you an AI thought leader

We are seeking a passionate and curious AI Platform Engineer (New Graduate) to help build operate and scale the next generation of AI infrastructure and platforms. This role is ideal for recent university graduates who are excited about cloud computing artificial intelligence machine learning platforms developer tools and large-scale distributed systems.

Its an opportunity that can make you an AI leader at BMO.

As an AI Platform Engineer you will work with experienced engineers and data scientists to create reliable secure and scalable platforms that enable AI applications and machine learning workloads across the organization.

This is an opportunity to learn from industry experts while contributing to cutting-edge AI solutions that drive real business impact.

• Build and maintain cloud-native platform services that support AI and machine learning workloads.
• Design and implement automation solutions using Infrastructure as Code (IaC).
• Develop tools APIs and services that improve developer productivity and platform reliability.
• Assist in deploying monitoring and scaling AI models and machine learning pipelines.
• Collaborate with software engineers data scientists and product teams to operationalize AI solutions.
• Monitor platform health and troubleshoot performance reliability and scalability issues.
• Contribute to CI/CD pipelines and DevOps practices for AI and platform engineering teams.
• Participate in system design discussions and code reviews.
• Learn and apply best practices around security observability governance and cloud architecture.

• Bachelors or Masters degree in Computer Science Software Engineering Computer Engineering Data Science or a related technical field completed within the last 12 months.
• Strong programming skills in one or more languages such as:
  • Python
  • Go
  • Java
  • C#
• Understanding of software engineering fundamentals including:
  • Data structures and algorithms
  • Object-oriented design
  • REST APIs
  • Version control (Git)
• Familiarity with Linux operating systems and scripting.
• Knowledge of cloud platforms such as Microsoft Azure AWS or Google Cloud Platform.
• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.

• Exposure to machine learning generative AI or large language models through coursework projects or internships.
• Experience with containers and orchestration technologies such as Docker and Kubernetes.
• Familiarity with MLOps concepts and tools.
• Understanding of CI/CD practices and automation.
• Experience with infrastructure-as-code tools such as Terraform.
• Contributions to open-source projects hackathons research or personal technical projects.

• AI platform architecture and operations at scale.
• Cloud-native application design and deployment.
• MLOps LLMOps and AI governance best practices.
• Platform engineering and site reliability engineering principles.
• Secure software development and enterprise cloud operations.

Were looking for individuals who:

• Are naturally curious and eager to learn.
• Enjoy solving challenging technical problems.
• Thrive in collaborative environments.
• Take ownership of their work and seek continuous improvement.
• Are excited about the future of AI and cloud technologies.
• Critical Thinking
• Building and managing relationships.
• Adaptability.
• Verbal & written communication skills.
• Collaboration & team skills.
• Analytical and problem solving skills.
• Data driven decision making.

Nice-to-Have Technical Skills

• Azure AI Services Azure Machine Learning or Azure Kubernetes Service (AKS)
• Kubernetes Docker Helm
• Terraform or Bicep
• GitHub Actions or Azure DevOps
• Prometheus Grafana OpenTelemetry
• PostgreSQL Redis or NoSQL databases
• LangChain Semantic Kernel or other AI frameworks
• Retrieval-Augmented Generation (RAG) concepts