Specialist System Engineering - DevOps Engineer — AI & Pipeline Automation

Lead the design, development, and maintenance of Azure DevOps CI/CD pipelines for 5G NF applications, incorporating AI‑driven automation to analyze failures, orchestrate self‑healing workflows, and provide actionable insights. Collaborate with client teams to architect robust DevOps solutions, build reusable YAML templates, and integrate Kubernetes deployments, observability, and secure DevOps practices.

• Design, build, and maintain repeatable, secure CI/CD pipelines on Azure DevOps.
• Develop AI‑assisted automation to analyze build failures, deployment issues, and pipeline health.
• Build and maintain MCP servers and AI‑callable tool integrations.
• Create self‑healing pipeline workflows with diagnostics and escalation paths.
• Partner with client project teams to understand requirements and architect solutions.
• Develop reusable YAML templates, pipeline components, scripts, and libraries.
• Integrate source control, artifact repositories, approvals, testing frameworks, and security checks.
• Support Kubernetes deployments, troubleshoot failures, and optimize performance.
• Implement observability for CI/CD systems with metrics, logs, dashboards, and alerts.
• Apply secure DevOps practices for secrets handling, access control, and audit readiness.
• Create AI‑assisted root‑cause analysis tools and knowledge workflows.
• Lead technical discussions, demos, and training sessions.
• Document architecture, procedures, and standards.
• Continuously evaluate emerging DevOps, GenAI, LLM, and MCP capabilities.

• Expertise in Linux administration and scripting with Bash, Python, and PowerShell.
• Proficient in Infrastructure as Code using Ansible.
• Deep experience building Azure DevOps pipelines from scratch with YAML, JSON, and Azure CLI.
• Hands‑on Kubernetes (AKS) deployment, kubectl, Helm, and RBAC.
• Knowledge of Azure services: ACR, ARM, Bicep, Key Vault, Azure Operator Service Manager.
• Experience integrating Azure OpenAI or equivalent LLM APIs into automation workflows.
• Ability to design and operate MCP servers for AI‑callable tools.
• Strong communication skills for technical presentations and stakeholder collaboration.