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Kiguli
DevOps & Infrastructure Engineer at Planet Systems (U) Limited
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Competencies
Specialized in designing, deploying, and optimizing cloud environments across AWS, GCP, and Azure.
Proficient in building CI/CD pipelines, scripting automation, and container orchestration to streamline deployments.
Experienced with Docker, Portainer, Traefik, and Kubernetes for scalable, reliable application hosting.
Skilled in Python, Node.js, and Bash scripting for automation, monitoring, and data analytics pipelines.
Education
Summary
Versatile DevOps professional with extensive experience in cloud architecture, automation, and container orchestration across multiple platforms. Adept at optimizing infrastructure costs and maintaining high uptime.
Key Achievements
- Maintained 99.9% uptime for critical development environments, ensuring seamless operations.
- Designed scalable cloud infrastructure for startups, reducing deployment times with automated CI/CD pipelines.
- Optimized multi-cloud workloads, reducing infrastructure costs by 15%.
- Deployed high-availability telemedicine clusters supporting remote USSD and data transactions.
Experience
DevOps & Infrastructure Engineer
Manage container fleets using Portainer and utilize Traefik for reverse proxy and load balancing across internal apps.. Maintain 99.9% uptime for active development environments by resolving network and application-layer performance bottlenecks.
Founding DevOps Engineer (Contract)
Designed the startup's core infrastructure on cloud, optimizing for rapid scale and low-latency logistics operations in Kenya.. Built automated CI/CD pipelines to slash deployment times and maintain high shipping velocity.
Software Developer / DevOps
Operated in a fast-paced hybrid role, writing Python automation scripts to monitor system health and drive data analytics pipelines.
Cloud Engineer (Consultant)
Deployed a highly available telemedicine cluster on Azure Kubernetes Service (AKS) supporting remote USSD and data sync transactions.
Associate Technical Lead
Optimized multi-cloud production workloads (AWS/GCP), reducing monthly infra spend by 15%.