AI Engineer / Intelligent Operations (Infrastructure)-7
Role summary
We are seeking an experienced AI Engineer specializing in Intelligent Operations for Infrastructure. This full-time, onsite role in Toronto focuses on designing and implementing AI/ML solutions to enhance infrastructure monitoring, automation, and operational efficiency. The engineer will work at the intersection of AI/ML, cloud infrastructure, and DevOps, developing models for predictive maintenance, automating incident response, building data pipelines, and integrating AI with cloud/on-prem platforms. Responsibilities include optimizing system performance, managing the ML model lifecycle via MLOps, and providing technical leadership.
Toronto, Ontario M5V 3L9 Posted March 29th, 2026
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Job Type: Full Time
Job Category: IT
Job Description
### Role: AI Engineer – Intelligent Operations (Infrastructure)
### Location: Toronto, ON
### Employment Type: Full-Time (FT)
### Work Mode: Onsite
## Job Description:
We are seeking an experienced AI Engineer – Intelligent Operations (Infrastructure) to design and implement AI-driven solutions that enhance infrastructure monitoring, automation, and operational efficiency. The ideal candidate will work at the intersection of AI/ML, cloud infrastructure, and DevOps to build intelligent operational systems.
## Key Responsibilities:
Develop and deploy AI/ML models for infrastructure monitoring and predictive maintenance
Automate incident detection, root cause analysis, and remediation workflows
Integrate AI solutions with cloud and on-prem infrastructure platforms
Build data pipelines for infrastructure logs and telemetry analysis
Collaborate with DevOps, SRE, and Cloud teams
Optimize system performance, scalability, and reliability
Implement MLOps practices for model deployment and lifecycle management
Provide technical leadership and documentation
## Required Skills:
Strong experience in Python and AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn)
Experience working with infrastructure monitoring data (logs, metrics, traces)
Knowledge of cloud platforms (AWS, Azure, or GCP)
Experience with Docker and Kubernetes
Understanding of DevOps and CI/CD practices
Strong analytical and problem-solving skills
## Preferred Qualifications:
Experience in AIOps or Intelligent Automation
Knowledge of monitoring tools (Splunk, Datadog, Prometheus, etc.)
Experience with MLOps tools (MLflow, SageMaker, Vertex AI)
Strong communication and stakeholder collaboration skills
Required Skills
DEVOPS ENGINEER
SENIOR EMAIL SECURITY ENGINEER