Posting record
Open 9+ days
- Xcellink's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Xcellink, so its true age is longer.
Last checked Nov 4, 2026.
How well do you match?
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Upload your resumeWhat it asks of you
- 3+ years of experience
What the posting discloses
Not stated: Pay, real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Some employers add pay only on their own site. Check the original posting before you rule it out.
Skills mentioned
About the role
We are looking for an experienced DevOps Engineer to design, build, and maintain scalable AI platforms that support enterprise AI, Machine Learning, and Generative AI initiatives. This role combines Cloud Engineering, DevOps, Platform Engineering, and MLOps, making it ideal for candidates passionate about automation, Kubernetes, cloud-native technologies, and AI platform operations.
You will work closely with cloud architects, infrastructure teams, and application developers to deliver secure, scalable, and highly available AI platforms.
Key Responsibilities
- Design, implement, and manage cloud infrastructure using Terraform and Infrastructure-as-Code (IaC) practices.
- Build and maintain AI platform environments across Azure and AWS .
- Develop and optimize CI/CD pipelines using Azure DevOps, GitHub Actions, GitLab CI, or Jenkins.
- Automate application and platform deployments using DevOps and GitOps methodologies.
- Support AI/ML and Generative AI workloads, including deployment, monitoring, and lifecycle management.
- Manage containerized environments using Docker and Kubernetes .
- Implement platform monitoring, logging, observability, security, and governance best practices.
- Support MLOps capabilities including model deployment, versioning, monitoring, and automation.
- Collaborate with engineering, security, and architecture teams to improve platform reliability and operational efficiency.
- Troubleshoot infrastructure, performance, security, and platform-related issues.
Requirements
- Diploma or Degree in Information Technology, Computer Science, Computer Engineering, or related discipline.
- Minimum 3 years of experience in DevOps, Cloud Engineering, Platform Engineering, or Infrastructure Automation.
- Strong hands-on experience with Terraform and Infrastructure-as-Code.
- Experience building and maintaining CI/CD pipelines .
- Strong knowledge of Docker and Kubernetes .
- Hands-on experience with Azure and/or AWS cloud platforms.
- Scripting experience in Python, PowerShell, Bash, or Shell scripting .
- Knowledge of Git, version control, and DevOps best practices.
- Experience supporting AI/ML platforms, MLOps environments, or Generative AI workloads is highly advantageous.
- Familiarity with Azure OpenAI, Azure Machine Learning, AWS Bedrock, or similar AI services is a plus.
- Experience with monitoring tools such as Prometheus, Grafana, Datadog, Splunk, or Azure Monitor.
- Cloud, Kubernetes, Terraform, DevOps, or AI-related certifications are advantageous.
Preferred Skills
- Kubernetes Administration
- GitHub Actions / GitLab CI / Jenkins
- MLOps and AI Platform Operations
- Infrastructure Automation
- Cloud Security & DevSecOps
- Generative AI Platform Deployment
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