AI/ML Engineer

ThoughtStorm; Canada; On-site; CAD 90,000 - 130,000; Full time

Job summary

A leading tech company in Canada is seeking an AIOps Engineer to architect, provision, and operationalize multi-environment AI platforms on Google Cloud. In this role, you will design cloud architectures, govern IAM, and develop CI/CD pipelines. Ideal candidates will demonstrate deep experience with Terraform and AIOps frameworks, along with proficiency in Python. The position demands strong skills in collaborating with diverse teams to optimize cloud environments, ensuring compliance and best practices are met.

Qualifications

• Deep experience with Terraform and Infrastructure as Code workflows.
• Practical experience with AIOps and MLOps frameworks.
• Proficient in Python for automation and monitoring jobs.

Responsibilities

• Conduct workshops to gather GCP environment requirements.
• Design cloud architecture including VPC, IAM, security controls.
• Lead the provisioning of GCP projects using Terraform.

Skills

Terraform

AIOps frameworks

MLOps frameworks

Python

CI/CD pipeline development

Education

GCP Professional ML Engineer or Cloud Architect certification

Tools

Google Cloud

Cloud Monitoring

OpenTelemetry

Job description

The AIOps Engineer is responsible for architecting, provisioning, and operationalizing multi-environment AI platforms on Google Cloud (Sandbox, Dev, Prod). The role includes cloud environment setup, IAM governance, CI/CD pipeline development, AIOps automation, drift detection, lifecycle process design, documentation, and alignment with broader enterprise platforms.

Responsibilities

• Conduct workshops to gather GCP environment requirements.
• Design cloud architecture including VPC, IAM, subnetting, quotas, endpoints, and security controls.
• Lead the provisioning of Sandbox, Dev, and Prod GCP projects using Terraform.
• Oversee API enablement, configuration, and validation testing.

Role Definitions IAM Governance

• Define IAM roles for AI platform users (Owner, Support, ML Engineer, Viewer).
• Create IAM matrices, RACI charts, and detailed access control documentation.
• Ensure least-privilege access policies across Vertex AI and GCP services.
• Coordinate reviews and approvals with security and architecture teams.

AIOps Framework Development

• Design and implement drift detection, anomaly monitoring, canary releases, automated rollback, and observability components.
• Build reusable CI/CD pipelines using Vertex Pipelines and Cloud Build.
• Develop SOPs, diagrams, runbooks, and the full AIOps operations playbook.
• Execute and validate synthetic drift, monitoring, and pipeline test scenarios.

Lifecycle Processes

• Define the complete ML lifecycle from environment setup through deployment, monitoring, retraining triggers, and retirement.
• Integrate lifecycle processes within CI/CD and AIOps automation.
• Document all lifecycle flows in Confluence and conduct validation sessions.
• Develop team structure, roles, and support plans.
• Build cost and usage models using GCP calculators and automation scripts.
• Prepare development and production usage forecasts and long-term TCO estimates.

Core Technical Skills

• Deep experience with Terraform and Infrastructure as Code workflows.
• Practical experience with AIOps and MLOps frameworks.
• Proficient in Python for automation and monitoring jobs.
• Experience designing and operating CI/CD pipelines for ML workloads.
• Knowledge of observability tools such as Cloud Monitoring, Logging, and OpenTelemetry.

Preferred Qualifications

• GCP Professional ML Engineer or Cloud Architect certification.
• Experience with Looker or other operational dashboards.