DevOPs Engineer

About the role

CGI is seeking an experienced Azure DevOps Engineer to design, implement, automate, and support secure, scalable cloud infrastructure and software delivery pipelines within the Microsoft Azure ecosystem. This is a hands-on engineering role responsible for enabling development teams to build, test, deploy, and operate applications efficiently and reliably. The ideal candidate has strong experience with Azure, CI/CD, Infrastructure as Code (IaC), containerization, Kubernetes, security, monitoring, and automation, and is comfortable supporting modern application, data, and AI workloads. The Azure DevOps Engineer will partner closely with software engineers, AI engineers, data engineers, architects, cybersecurity teams, and product teams to establish DevOps standards, automate delivery processes, improve developer productivity, and maintain reliable cloud environments. This role is located in Plano, TX.

Responsibilities

• Design, implement, and support secure, scalable cloud infrastructure within the Microsoft Azure ecosystem
• Build, maintain, and optimize CI/CD pipelines for application deployment
• Automate delivery processes and improve developer productivity
• Establish DevOps standards and maintain reliable cloud environments
• Instrument distributed systems and establish actionable alerting
• Deploy and operate GenAI and agentic workloads in production
• Support data infrastructure including Delta Lake, PostgreSQL, MongoDB, and streaming platforms (Kafka, Event Hubs)
• Operate large production applications including capacity planning for high concurrency workloads
• Define SLOs and participate in incident response
• Optimize compute and inference spend

Required Skills

• Deep hands-on experience with Microsoft Azure, including AKS, Container Apps or App Service, Azure Functions, API Management, Key Vault, Storage, and core networking
• Proven experience provisioning and managing cloud infrastructure declaratively using Terraform and/or Bicep/ARM, with reusable modules, state management, and environment promotion strategies
• Strong experience building, hardening, and deploying containerized workloads on Kubernetes/AKS, including Helm charts, resource tuning, horizontal and cluster autoscaling, and ingress configuration
• Experience designing and maintaining multi-stage CI/CD pipelines in Azure DevOps or GitHub Actions, covering build, test, security gates, artifact management, and progressive deployment (blue-green or canary)
• Proficiency in Python for automation, tooling, and operational scripting
• Ability to read and debug application code written by the engineering team
• Hands-on experience with Azure Monitor, Application Insights, and Log Analytics (KQL), and/or Prometheus, Grafana, and OpenTelemetry
• Ability to instrument distributed systems and establish actionable alerting
• Experience deploying and operating GenAI and agentic workloads in production, Azure OpenAI or Azure AI Foundry, model and prompt versioning, evaluation and regression pipelines, vector database operations, and monitoring of token usage, latency, and inference cost
• Working experience with Databricks and MLflow for model lifecycle management
• Comfort supporting data infrastructure such as Delta Lake, PostgreSQL, MongoDB, and streaming platforms including Kafka or Event Hubs
• Practical experience with Microsoft Entra ID, managed identities, RBAC, secrets and certificate management, DevSecOps scanning, and network isolation patterns for sensitive workloads
• Proven experience operating large production applications, including capacity planning for high concurrency workloads, defining SLOs, incident response, and optimizing compute and inference spend
• Demonstrated ability to deliver in short iteration cycles alongside rapidly evolving requirements, balancing speed with the platform stability and guardrails that production AI systems require
• Excellent problem solving abilities, attention to detail, ownership under ambiguity, and strong communication skills across engineering, data science, and business stakeholders

Preferred Qualifications

• Agentic Frameworks: Familiarity with LangChain/LangGraph, Semantic Kernel, or Model Context Protocol (MCP), and the operational patterns of multi-agent and tool calling systems
• GitOps: Experience with ArgoCD or Flux for declarative, Git-driven cluster management
• API Layer: Exposure to Istio, Linkerd, or equivalent, plus API gateway and rate limiting patterns for LLM-backed endpoints
• FinOps: Experience with cloud cost attribution, chargeback, and GPU or token consumption optimization
• Familiarity with Node.js build tooling and front-end deployment workflows (React, Next.js) is a bonus
• Specific industry/domain knowledge relevant to telecommunications is preferred