Cloud/AI Platform Engineer

BMO•Toronto, ON

5d•CA$75,900 - CA$141,900•Hybrid

About The Position

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. 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.

Requirements

Bachelor's or Master's 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.

Nice To Haves

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.
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

Responsibilities

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.