Girish Kumar Reddy Moore
Technology / Internet
Social Networks
Services offered
I’m a DevOps and observability engineer with over 6 years of experience in building, automating, and optimizing cloud-native infrastructure across Azure, AWS, and GCP. My expertise spans CI/CD pipelines, Terraform, Helm, Kubernetes, and cloud observability stacks (Prometheus, Grafana, Loki, Tempo, Mimir, OpenTelemetry, Datadog, Splunk, and New Relic).
I’m passionate about designing end-to-end observability architectures and implementing platform reliability, automation, and security at scale. Recently, I’ve been expanding into AI Observability, AIOps, and LLMOps, focusing on integrating RAG pipelines, vector databases, and telemetry insights to enhance AI-driven operations.
I enjoy solving complex infrastructure challenges, building self-healing systems, and continuously learning emerging technologies. I’m currently exploring opportunities where I can contribute to platform engineering, cloud observability, or AI-driven DevOps initiatives, preferably in a remote-first environment.
Experience
Results-driven DevOps and Observability Engineer with over 6 years of experience in designing, automating, and managing cloud-native infrastructure across Azure, AWS, and GCP. Skilled in CI/CD pipeline development (Azure DevOps, GitHub Actions, Jenkins), Infrastructure as Code (Terraform, Helm, Bicep), and container orchestration using Kubernetes.
Expert in implementing end-to-end observability solutions using Grafana, Prometheus, Loki, Tempo, OpenTelemetry, and Splunk, enabling proactive monitoring, alerting, and performance optimization. Adept at improving system reliability, scalability, and security through automation and best practices.
Currently expanding expertise in AI Observability, LLMOps, and AIOps, focusing on integrating telemetry and automation into intelligent cloud operations.
Education
Completed multiple advanced hands-on training in Azure, AWS, Kubernetes, Terraform, and DevOps practices, along with continuous learning in observability, AIOps, and LLMOps to stay aligned with modern platform engineering trends.
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