Baku, Baku Ekonomic Zone, Azerbaijan
I turn AI investments into production reality — autonomous agents, real Kubernetes clusters, real numbers. $0.004 per incident. 70% infrastructure savings. 6-second response time. 15 years in infrastructure (Linux, DevOps, Cloud, Data Architecture) — now building at the intersection of Platform Engineering and AI. What I've built: → 4-agent pipeline for Kubernetes incident response (Detector → Researcher → Judge → Executor) → SafeScale AI — autonomous FinOps orchestrator with hybrid cloud/local failover → MCP server wrapping kubectl — 6 tools, 146 lines, real production cluster → $200 total spent vs $150,000/year commercial AIOps alternative Infrastructure expertise: → Cloud: GCP · AWS · Azure · bare-metal (Hetzner) → Orchestration: Kubernetes · Docker · Helm → IaC: Terraform · Ansible · GitLab CI/CD · GitHub Actions → Observability: Prometheus · Grafana · Loki · AlertManager → Data: ClickHouse · Airflow · MinIO · DataOps pipelines → AI/LLM: Claude API · Anthropic SDK · Ollama · RAG · MCP Core practices: DevOps · GitOps · DataOps · Platform Engineering · SRE · FinOps With a strong background in Linux administration, networking, and security across production-grade environments — cloud, hybrid, and on-premises. 📢 t.me/devops_to_ai 📝 medium.com/@ahmad.gayibov 🐙 github.com/absence77 #AIAgents #Kubernetes #DevOps #PlatformEngineering #LLM #SRE #FinOps #CloudInfrastructure