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Added 3 mins ago
AI
Kafka Developer/ Engineer
Apptoza Inc.
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- Contract
Added 3 mins ago
A
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Added 33 mins ago
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Associate – Front Office Quant Engineer
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Added 33 mins ago
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Added 33 mins ago
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Data Engineer
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Added 33 mins ago
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Added 35 mins ago
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AI Engineer
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Added 1 hour ago
M
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Toronto, ON
- Full-time
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Systematix

Senior DevOps Engineer – AI & Data Platform

Canada

Contract

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Job details

Job type: Contract
Experience: Extensive senior-level (10+ years) DevOps engineering experience within complex enterprise environments.
Posting language: English
Posted: Oct 5, 2026

Original job description

We are Systematix and we are currently looking for a Senior DevOps Engineer – AI & Data Platform to help modernize and automate the engineering practices supporting a rapidly growing enterprise AI and Data ecosystem for one of our key clients.

ABOUT THE PROJECT

Our client is a global leader in science and technology, supporting a diverse portfolio of businesses across healthcare, life sciences, diagnostics, manufacturing and industrial innovation. As investment in AI, machine learning and advanced data capabilities continues to accelerate, the organization is modernizing the engineering practices and automation required to support these workloads at enterprise scale.

The primary objective is to eliminate manual infrastructure, build and deployment processes and replace them with automated, repeatable and reliable engineering pipelines. Working closely with Platform Engineering, MLOps and other technical teams, the successful candidate will help establish modern DevOps patterns and standards while remaining highly hands-on in their implementation.

ABOUT THE RESPONSIBILITIES

Design, build and maintain CI/CD pipelines supporting cloud infrastructure, applications and AI/ML workloads.
Provide hands-on operational support for DevOps/platform services, working within established ticketing, incident management and escalation processes to troubleshoot and resolve infrastructure, pipeline and deployment issues.
Implement Infrastructure as Code and automated Azure cloud provisioning.
Create standardized and repeatable Development, UAT and Production deployment patterns.
Automate application and infrastructure testing, validation, deployment and release processes.
Develop reusable engineering tooling, templates and automation components.
Integrate infrastructure and deployment automation with GitHub-based development workflows.
Design and implement GitHub Actions or equivalent CI/CD workflows.
Support containerized applications and workloads using Docker and Kubernetes.
Partner with Platform Engineering teams to automate Azure infrastructure provisioning and deployment.
Partner with MLOps engineers to automate machine learning lifecycle, deployment and operational processes.
Build self-service capabilities that enable development, data science and machine learning teams to deploy and consume technology with minimal manual intervention.
Identify manual engineering processes and replace them with scalable, code-driven automation.
Improve deployment speed, consistency, repeatability, reliability and overall developer experience.
Implement appropriate security, governance and operational controls within automated engineering processes.
Help establish modern SDLC, DevOps, source control, deployment and engineering standards.
Provide technical leadership and recommendations while remaining directly involved in engineering, coding, configuration and implementation.

ABOUT THE REQUIREMENTS

Extensive senior-level (10+ years) DevOps engineering experience within complex enterprise environments.
Strong hands-on experience with Microsoft Azure.
Experience operating within enterprise support models, including ticket queues, incident management, troubleshooting, escalation procedures and coordination across technical support teams.
Demonstrated expertise with Infrastructure as Code and automated cloud provisioning.
Strong experience designing, building and maintaining enterprise CI/CD pipelines.
Hands-on experience with GitHub, GitHub Actions or comparable Git-based CI/CD technologies.
Strong experience with Docker, Kubernetes and containerized workloads.
Advanced scripting and automation capabilities.
Strong understanding of modern SDLC, source control, release management and deployment practices.
Experience developing reusable automation, engineering templates, deployment patterns and tooling.
Experience integrating infrastructure automation with application development and deployment workflows.
Demonstrated experience transforming relatively manual or immature engineering environments into automated, repeatable and code-driven platforms.
Strong troubleshooting and problem-solving capabilities.
Ability to operate effectively as both a senior technical advisor and hands-on engineer.
Strong communication and collaboration skills with the ability to work across DevOps, Platform Engineering, MLOps, cloud, security, data and application engineering teams.

PREFERRED QUALIFICATIONS

Experience supporting infrastructure and deployment processes for AI and machine learning workloads.
Experience with Azure Machine Learning and related Azure AI/data services.
Experience working with MLOps engineering practices and machine learning deployment pipelines.
Experience supporting GPU or accelerated computing environments.
Strong Python development or scripting experience.
Experience with Platform Engineering and internal developer platforms.
Experience creating self-service engineering and deployment capabilities.
Experience working within large, global or federated enterprise environments.
Experience helping establish DevOps capabilities, standards and practices within an immature or evolving engineering environment.

ABOUT THE ROLE

This is a contract opportunity supporting a strategic enterprise AI, Data and Cloud engineering initiative.This is a senior, highly hands-on engineering role. The successful candidate will help define DevOps architecture, standards and engineering patterns while personally building and implementing the pipelines, automation and tooling required to put those standards into practice.

We are looking for an engineer who naturally approaches manual infrastructure and deployment processes as opportunities for automation and who is equally comfortable defining the solution and sitting down to build it.

AI DISCLOSURE

As part of our recruitment process, Systematix may use artificial intelligence (AI) tools to assist with resume screening, candidate matching and recruitment administration. All hiring decisions are ultimately made by our recruitment and hiring teams.

APPLY NOW

If you are interested in finding out more, please contact us or submit your resume to jobs@systematix.com.

Know someone who would be a great fit? We welcome referrals of qualified candidates and are always interested in connecting with talented technology professionals.

ABOUT SYSTEMATIX

Systematix is a Canadian-owned Global Consulting and Resourcing firm with nearly 50 years of experience delivering technology solutions to clients across North America and the United Kingdom. We provide the highest-caliber consulting solutions to a diverse client base across all levels of government and private industry. Systematix is committed to creating a diverse, inclusive environment and is proud to be an equal opportunity employer. At Systematix, we value diverse perspectives, experiences, and backgrounds.

Systematix. Solutions Focused. People Driven.

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More about this job

Responsibilities

Design, build, and maintain automated CI/CD pipelines, Azure infrastructure provisioning, and repeatable deployment patterns for applications and AI/ML workloads. Develop reusable tooling and self-service capabilities, troubleshoot platform and deployment issues, and establish secure DevOps standards in collaboration with Platform Engineering and MLOps teams.

Requirements

Requires 10+ years of senior DevOps experience, strong hands-on Azure, Infrastructure as Code, CI/CD, GitHub-based workflows, Docker, Kubernetes, and advanced scripting and automation skills. Candidates should be experienced in enterprise support and troubleshooting, transforming manual processes into automated platforms, and providing technical leadership while remaining hands-on.

Skills

Azure
DevOps
CI/CD
Infrastructure As Code
GitHub Actions
Docker
Kubernetes
Scripting And Automation
Python
MLOps
Azure Machine Learning
Cloud Provisioning
Pipeline Troubleshooting
Release Management
Platform Engineering
Machine Learning Deployment

Visa sponsorship

Not detected in the job text

Keywords

Azure
Azure Machine Learning
AI
Machine Learning
Data Platform
DevOps
MLOps
CI/CD
Infrastructure As Code
GitHub
GitHub Actions
Docker
Kubernetes
Python
Cloud Provisioning
Automation
Platform Engineering
Internal Developer Platforms
Self-Service Capabilities
Development, UAT, And Production
SDLC
Source Control
Release Management
Deployment Pipelines
Incident Management
Ticketing
GPU Computing
Security Controls
Governance
Enterprise Engineering

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