Ismail Y.

• Designed and operated OpenStack private, AWS, GCP and public cloud infrastructure supporting over 2000 virtual machines and dozens of enterprise customers, ensuring high availability, capacity planning, and operational excellence. • Modernized cloud automation platform by migrating legacy Rundeck workflows into Argo Projects (Workflows + Events), eliminating $250K+ yearly licensing costs and improving execution reliability and visibility. • Designed and automated full lifecycle operations for 400+ AWS, GCP and OpenStack nodes, including implementing Ubuntu ESM upgrades and driving the platform migration to Ubuntu 24.04. Built a modern AMI pipeline using Packer and Ansible, replacing legacy images and improving patch consistency across environments. Additionally, refactored and modernized Chef cookbooks, reducing configuration drift and cutting manual operational workload by 60%, while lowering critical vulnerabilities by 40% within one quarter. • Implemented production AI for incident response (AWS DevOps Agent): Architected the reusable Terraform module and MCP-server integrations (Grafana, Datadog, PagerDuty, CloudWatch) that provision the AI agent, and built GitHub Actions CI/CD to validate and continuously deploy its AI investigation skills — cutting root-cause time to under 15 minutes. • Built a self-service Dashboard-as-Code platform (Grafonnet/Jsonnet + Tekton CI/CD) that lets engineering teams define Grafana dashboards and alerts as JSON, auto-generating and deploying production-ready observability across multiple environments — eliminating manual dashboard setup. • Modernized the CI/CD platform by migrating from Codeship to GitHub Actions, cutting pipeline execution times by 35% and ensuring business continuity following Codeship's end-of-life. Implemented and managed Gomboc AI integration for Terraform repositories, introducing automated Infrastructure-as-Code security scanning, policy governance, and AI-assisted remediation workflows. • Built core Terraform modules and platform blueprints enabling standardized EKS cluster provisioning, IAM guardrails, and baseline workloads—reducing new-account onboarding time from weeks to 3 days. • Strengthened cloud security posture through SIEM integrations, proactive vulnerability remediation (Qualys/SSM), and automated compliance checks, improving MTTR for high-severity findings by 30%. • Developed AI-assisted operational frameworks using MCP (Model Context Protocol) to connect cloud platforms, security tools, and monitoring systems—enabling LLM-driven remediation guidance, automatic patching workflows for cloud instances, and significantly faster troubleshooting across environments instead of human intervention. • Leveraged AI engineering tools (ChatGPT, Claude, Cursor) to accelerate documentation, build optimized Terraform/Helm templates, and troubleshoot complex issues, improving engineering throughput by 20–30%. • Provided technical leadership and mentorship, guiding junior and mid-level engineers on Kubernetes, Terraform, cloud security, and architecture best practices—resulting in improved team velocity and higher-quality outputs. • Collaborated with cross-functional teams (Platform, QA, App Teams, Infosec) to define unified automation strategies, streamline deployments, and standardize infrastructure across environments. • Enhanced documentation and operational readiness by creating runbooks, architectural diagrams, onboarding guides, and troubleshooting playbooks—reducing onboarding time by 20% and improving operational consistency.