I'm an infrastructure-focused software engineer who has worked developing enterprise-scale and Payment Card Industry-compliant IaC modules at Visa and was responsible for the coordination and rollout of centralized cost monitoring in 45 production GCP projects, calculating 10% savings recommendations.
Recently I architected and built an AWS environment with data residency for pharmaceutical research, with an extreme multi-label (1.4k) classification NLP ingest pipeline.
Early career engineer with a passion for infrastructure, cycling (last summer riding 3030 miles from CO to LA!) and airplanes. Excited to learn and grow in a skilled team!
I've been watching these guys for so long — when Wren's speaking to camera in his solo videos he overdoes it but I think he's naturally pretty excitable. Niko is my favorite though.
I’m a few years older and in total admiration of you. Just from writing this comment I’m sure you’re already a great role model (at least you are to me!) I hope you get where you want to go too :)
Hi — I'm a CS student at the University of Edinburgh, graduating in May. Looking for backend/infrastructure/DevOps roles in the US.
I learned Linux through years of homelabbing and have professional experience in AWS and Terraform from a DevOps internship. I'm also interested in backend SWE — my dissertation project is implementing an aircraft tracking platform using ADS-B data, Kafka, MongoDB, GraphQL and Go.
Remote: Yes
Willing to relocate: Yes
Technologies: AWS, GCP, Terraform, Terragrunt, Pulumi, Ansible, Typescript, Python, Go, Kubernetes
Résumé/CV: https://copey.dev/copeland-royall-resume.pdf
Email: copeland [at] copey.dev
I'm an infrastructure-focused software engineer who has worked developing enterprise-scale and Payment Card Industry-compliant IaC modules at Visa and was responsible for the coordination and rollout of centralized cost monitoring in 45 production GCP projects, calculating 10% savings recommendations.
Recently I architected and built an AWS environment with data residency for pharmaceutical research, with an extreme multi-label (1.4k) classification NLP ingest pipeline.
Let me know if you think I could be a fit!
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