Specialist System Engineering - DevOps Engineer — AI & Pipeline Automation

Job Responsibilities   • Design, build, and maintain Azure DevOps CI/CD pipelines that support 5G NF application deployment from lab environments through production with repeatable, secure, and automated promotion workflows.    • Develop AI-assisted pipeline automation capabilities that use LLMs to analyze build failures, deployment issues, pipeline health, and operational telemetry.   • Build and maintain MCP servers and AI-callable tool integrations that expose Azure, Azure DevOps, Kubernetes, repository, and deployment capabilities through controlled automation interfaces.   • Create self-healing pipeline workflows that can detect common failure patterns, trigger approved remediation steps, and provide clear diagnostics, confidence levels, and escalation paths.   • Partner with client project teams to understand delivery requirements, architect CI/CD solutions, and implement automation patterns aligned with enterprise DevOps standards.   • Develop reusable YAML templates, pipeline components, scripts, and automation libraries that standardize CI/CD delivery across applications, environments, and teams.   • Integrate pipeline workflows with source control, artifact repositories, approvals, environment gates, testing frameworks, security checks, and release governance processes.   • Support Kubernetes-based deployments by troubleshooting deployment failures, configuration issues, container readiness, service health, and environment-specific pipeline behavior.   • Implement observability for CI/CD systems, including pipeline metrics, logs, dashboards, alerts, failure trend analysis, and continuous improvement feedback loops.   • Apply secure DevOps practices for secrets handling, access control, policy enforcement, code review, vulnerability checks, and audit-ready release execution.   • Create AI-assisted root-cause analysis tools and knowledge workflows that help engineering teams quickly identify probable causes and recommended next actions.   • Lead technical discussions, working sessions, demos, and hands-on training to improve DevOps maturity and enable client teams to adopt AI-enabled pipeline automation.   • Document architecture, operating procedures, automation patterns, troubleshooting guides, and standards to ensure consistent adoption and long-term maintainability.   • Continuously evaluate emerging DevOps, GenAI, LLM, and MCP capabilities and recommend practical enhancements that improve delivery speed, quality, reliability, and operational efficiency.     Job Qualifications / Required Qualifications   Linux & Scripting Fundamentals   • Expert-level Linux experience with strong scripting skills in Bash, Python, and/or PowerShell   • Proven ability to automate manual processes using scripting languages and Infrastructure as Code (e.g., Ansible)   • Hands-on experience containerizing, deploying, debugging, and maintaining applications     Azure DevOps & Pipeline Engineering   • Expert ability to build ADO Pipelines from the ground up using YAML   • Proficiency with az cli commands within ADO Pipelines to interact with Azure Resources   • Deep understanding of ADO Repos including branching, tagging, and environment management strategies   • Working knowledge of ADO Agents – their purpose, capabilities, and limitations   • Strong use of JSON and YAML as data formats across scripts, Ansible playbooks, and pipelines     Azure Platform & Infrastructure   • Experience with Azure Container Registry (ACR) to import, tag, and extract images and charts within pipelines   • Understanding of Azure Resource Manager, Endpoints, and Service Principals   • Ability to build Azure Resources using Bicep and ARM Templates with emphasis on parameterization   • Familiarity with Azure Key Vault (AKV) and Hash