Client: Aerospace/Defence Industry

Job Title: Senior Azure DevOps / AI Platform DevOps Specialist

Location: Ottawa, ON

Contract Duration: 12 months with possibility for extension or conversion to permanent

Schedule: Hybrid, 3 days in office, 2 days' work from home. Core hours are 9:30am–3pm

local time (somehow flexible) can start as early as 7:30

Maximum Pay Rate: $89.30/hour as T4

Clearance Requirement: Secret

Role Overview: We are looking for a Senior Azure DevOps / AI Platform DevOp to join our

DevOps team. This role is specifically focused on managing and optimizing applications

deployed within the Microsoft Azure cloud environment with a focus on AI workflow

Must-Have Requirements:

- Experience: Minimum 5 years of relevant experience in DevOps or Cloud

Engineering roles.

- Azure Expertise: Significant expertise in Microsoft Azure cloud services and

deployments.

- Must have expertise in AI workflow ( experience supporting AI/ML or Agentic AI

workloads in production)

- CI/CD: A proven track record of building and supporting CI/CD pipelines within

enterprise environments.

- Automation: Strong scripting and automation skills, with a specific focus on Python.

Nice-to-Have Skills:

- Infrastructure as Code (IaC): Hands-on coding experience with Terragrunt and

Terraform.

- Testing: Experience integrating automated testing into the deployment lifecycle.

- Process Management: Experience implementing and managing comprehensive

DevOps processes and best practices.

Description

We are seeking an experienced Senior Azure DevOps / AI Platform DevOps Contractor to

join our team. The ideal candidate will bring deep expertise in Azure cloud deployment,

up-to-date GitLab CI/CD practices, and hands-on experience with Kubernetes or OpenShift.

Strong proficiency in Python scripting and automation is required, along with experience in

networking, security, and enterprise integrations. Experience supporting or deploying

AI/ML workloads into production is highly desirable.

Key Responsibilities

- Implement and optimize DevOps practices within an Azure cloud environment, ensuring

security, scalability, resilience, and reliability.

- Design, build, and maintain robust GitLab CI/CD pipelines to accelerate software

delivery, infrastructure automation,



and production deployment. - Support the deployment and operation of containerized workloads using Kubernetes

and/or OpenShift, applying platform engineering and operational best practices. - Contribute to the design and delivery of AI/Agentic AI DevOps capabilities, enabling

secure, production-ready deployment of AI workloads and supporting associated

infrastructure and controls.

- Drive automation for infrastructure provisioning, configuration, and deployment using

Infrastructure as Code principles and repeatable engineering practices. - Collaborate closely with development, operations, security, and enterprise platform

teams to troubleshoot and resolve complex live performance, stability, and integration

issues, while implementing preventative improvements.

- Support release planning, deployment scheduling, and operational readiness for cloud

hosted and AI-enabled applications.

- Provide technical guidance and recommendations to engineering teams based on

operational analysis, observability data, and platform monitoring insights.

- Ensure solutions align with enterprise requirements for security, authentication, access

control, governance, and integration with corporate systems.

- Stay current with emerging DevOps, Azure, Kubernetes, and AI platform technologies,

sharing knowledge and mentoring team members where appropriate.

Key Requirements

- Proven experience deploying, managing, and optimizing applications and platforms in Microsoft Azure.

- Strong hands-on experience with Kubernetes, including cluster operations, workload deployment, and platform best practices.

- Robust understanding of networking and security, particularly in cloud and containerized environments.

- Demonstrated success designing and maintaining GitLab CI/CD pipelines for enterprise scale applications and services.

- Strong scripting and automation capability using Python,



with Bash or similar scripting

also desirable.

- Experience integrating solutions with enterprise systems, including identity, authentication, and access management components.

- Strong troubleshooting skills with a proactive approach to reliability, operational support,

and continuous improvement.

- Ability to communicate effectively with both technical and non-technical stakeholders.

- Desirable experience supporting AI/ML or Agentic AI workloads in production.

Desirable Skills

- Experience implementing data governance and control frameworks.

- Experience using HashiCorp Vault for secrets management.

- Experience using and securing S3-compatible object storage, such as MinIO.

- Experience creating and optimizing production-grade GitLab CI/CD workflows.

- Strong experience in Kubernetes cluster administration and operational best practices.

- Expert knowledge of Kubernetes deployments using Helm.

- Experience with NVIDIA GPU Operator and GPU features such as time-slicing and MIG

slicing.

- Experience with LDAP and SSO authentication flows.

- Experience building and securing Docker images.

- Strong scripting capability in Bash and Python.

- Experience implementing RBAC controls, particularly in environments handling sensitive

data.

- Experience implementing security and compliance tooling, including vulnerability

scanning and SAST.

- Experience using tools such as Prometheus and Grafana for monitoring, observability,

and audit support.

- Experience designing and implementing highly available systems.

Pay: $89.30 per hour

Application question(s):

- Do you have a proven track record of building and supporting CI/CD pipelines in enterprise environments?
- Do you have experience in deploying and managing containerized applications at scale?
- Are you Azure DevOps Engineer Expert or related Azure certified?
- Do you have certifications in Kubernetes (CKA/CKAD), OpenShift, or DevOps tools are an advantage?
- Do you have experience supporting AI/ML or Agentic AI workloads in production?

Experience:

- DevOps or Cloud Engineering with significant Azure : 5 years (required)

Licence/Certification:

- Secret Clearance? (required)

Work Location: Hybrid remote in Ottawa, ON

📌 Senior Azure DevOps / AI Platform DevOps Specialist (Ottawa)
🏢 Morson Talent (Canada & USA)
📍 Ottawa