Infrastructure and DevOps professional focused on building, automating and operating reliable technology environments.
My experience includes Linux and Windows environments, infrastructure support, monitoring, troubleshooting, automation, virtualization, networking and operational processes.
I work with technologies such as Linux, Docker, Git/GitLab, Jenkins, Zabbix, Grafana, Shell/Bash, n8n, virtual machines, VPS, pfSense and SSL/TLS certificates.
My professional direction combines Infrastructure, DevOps and Cloud, with a growing specialization in MLOps and AI infrastructure.
Virtual Machines • VPS • VPN • SSL/TLS • Network Troubleshooting
Building practical knowledge around:
- Containerization with Docker
- CI/CD pipelines
- Infrastructure automation
- Linux administration
- Cloud infrastructure
- Infrastructure as Code
- Monitoring and observability
- Reliable and scalable environments
Expanding my engineering focus toward:
- Machine Learning fundamentals
- Deep Learning
- Model lifecycle
- ML pipelines
- Model serving
- Monitoring ML workloads
- Infrastructure for AI applications
- MLOps practices
The goal is to connect proven DevOps and Cloud engineering principles with the infrastructure and operational requirements of modern AI workloads.
Scripts and automation solutions focused on reducing manual operational tasks, improving reliability and standardizing infrastructure processes.
Monitoring solutions, dashboards and operational visibility using Zabbix and Grafana.
Practical projects involving Docker, containerized applications, CI/CD and infrastructure automation.
Projects exploring Machine Learning, Deep Learning and the engineering practices required to deploy, operate and monitor AI workloads.
- Automation First
- Infrastructure as Code
- Observability
- Reliability
- Scalability
- Reproducibility
- Clean Code
- Continuous Improvement