DevOPSCloud Engineer Senior

Toronto - Canada

Monthly Salary: Not Disclosed

Posted on: 5 hours ago

Vacancies: 1 Vacancy

Job Summary

Assignment: RQ00613 - DevOPS/Cloud Engineer - Senior

Requisition: RQ00613

Job Title: DevOPS/Cloud Engineer - Senior

Client: Supply Ontario

Start Date:

End Date:

Department: Operations

Office Location: Toronto

Business Days: 180.00

Location: Fully Remote

Public Sector Experience: No

Must Haves:

10 years experience Design and implement robust CI/CD pipelines using Azure DevOps Git and YAML
10 years experience Lead deployment of AI/ML models into production using automated pipelines
10 years experience Implement model lifecycle management (training validation deployment monitoring)
10 years experience Design and build data pipelines using Azure Data Factory Databricks and ADLS

Description

Experience: 10 years in IT 5 years in DevOps / Data Engineering / MLOps

Role Overview

We are seeking a highly skilled Senior DevOps / MLOps / Data Engineer to lead platform engineering deployment automation and AI/ML model deployment on Azure. This role emphasizes DevOps excellence secure and cost-efficient deployments and production-grade AI delivery while supporting ML lifecycle management and scalable data engineering solutions.

Deliverables

DevOps Deployment & MLOps (Primary Focus)
- Design and implement robust CI/CD pipelines using Azure DevOps Git and YAML
- Manage end-to-end deployment pipelines across Dev QA and Prod environments
- Lead deployment of AI/ML models into production using automated pipelines
- Deploy version and manage AI models (batch and real-time inference)
- Implement model lifecycle management (training validation deployment monitoring)
- Automate infrastructure provisioning using ARM/Bicep/Terraform
- Manage Azure resources via Azure Portal CLI and scripting
- Oversee cluster management (Databricks clusters scaling performance tuning)
- Implement release strategies versioning rollback and environment parameterization
- Develop scalable inference endpoints and API-based model serving
- Integrate AI services such as Azure AI Search and Azure AI Foundry
- Integrate and deploy services using REST APIs
- Monitor model performance drift and retraining strategies
- Ensure platform reliability monitoring and incident response
Data Engineering
- Design and build data pipelines using Azure Data Factory Databricks and ADLS
- Develop and optimize data models in Azure SQL SQL Server and Oracle
- Implement ETL/ELT processes for large-scale data processing
- Ensure data quality governance and performance optimization
- Support medallion architecture (Bronze Silver Gold layers)
Security & Compliance
- Implement secure cloud architecture using RBAC Managed Identities and Azure Key Vault
- Secure data pipelines storage and ML endpoints (encryption network controls private endpoints)
- Ensure compliance with data protection standards (PII handling auditability governance)
- Manage secrets credentials and access policies across environments
- Optimize cloud costs across Databricks storage and compute resources
- Implement cluster right-sizing auto-scaling and job vs all-purpose cluster strategies
- Monitor usage and enforce cost governance across environments
- Recommend architecture improvements for cost-performance balance
API & Integration
- Design and build scalable REST API layers for data access and model inference
- Develop and manage API-based integration patterns across internal systems and external vendors
- Enable real-time and batch integration with downstream applications
- Implement API security (authentication throttling versioning)
- Support integration with event-driven systems and messaging frameworks

Required Skills & Qualifications

Minimum 10 years of IT experience with 5 years in DevOps / MLOps / Data Engineering
Strong expertise in:
Azure ecosystem (ADF Databricks ADLS Azure SQL)
CI/CD pipelines Git and YAML-based deployments
Infrastructure as Code (ARM Bicep Terraform)
SQL and relational databases (Azure SQL Oracle)
REST API development and integration
Proven experience in:
- Deploying AI/ML models to production environments
- End-to-end deployment pipelines and release management
- Cluster management and optimization

Additional Terms

Nice to Have / Bonus

Experience with Azure AI Search and Azure AI Foundry
Experience with event-driven architecture (Event Grid Service Bus)
Exposure to streaming platforms (Kafka Event Hubs)
Knowledge of containerization (Docker Kubernetes AKS)
Experience with LLMs / Generative AI pipelines and prompt orchestration
Familiarity with data governance and medallion architecture

Soft Skills

Strong problem-solving and troubleshooting abilities
Ability to work across DevOps Data and ML teams
Excellent communication and documentation skills
Leadership and mentoring capabilities

Assignment: RQ00613 - DevOPS/Cloud Engineer - Senior Requisition: RQ00613 Job Title: DevOPS/Cloud Engineer - Senior Client: Supply Ontario Start Date: End Date: Department: Operations Office Location: Toronto Business Days: 180.00 Location: Fully Remote Public Sector Experience: No Must Haves: 1...