AI ML And Cloud Infrastructure Architect & DevOps at Toffee AI
Yerevan, Armenia
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Summary
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Rockstar
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Top School
Nikita Shupeyko is an AI/ML and cloud infrastructure architect with 10 years of experience designing highly available AWS, GCP, and Azure systems and driving DevOps excellence across startups and SMEs. He has repeatedly delivered large cost and reliability wins—architecting multi-environment Terraform-driven platforms, reducing cloud spend by up to 7x for clients, and contributing to $1M+ in client savings. A hands-on Python/Django backend engineer, he builds production-ready ML and microservice infrastructures, CI/CD pipelines, and developer tooling, and has added practical fixes and workflow improvements to the popular Cookiecutter Django project. Comfortable leading teams and consulting across the stack, he pairs strong communication with deep technical troubleshooting (e.g., resolving cert-manager/AKS TLS issues) to accelerate delivery and developer experience. Based in Yerevan, he blends formal training in applied mathematics and systems engineering with a pragmatic focus on observability, security, and reproducible ML deployments.
10 years of coding experience
8 years of employment as a software developer
Master's degree System & Software Engineering, Master's degree System & Software Engineering at Higher School of Economics
Bachelor's degree Applied Mathematics & Computer Science, Bachelor's degree Applied Mathematics & Computer Science at National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)
Cookiecutter Django is a framework for jumpstarting production-ready Django projects quickly.
Role in this project:
Backend & DevOps Engineer
Contributions:174 commits, 327 PRs, 411 pushes in 1 year 4 months
Contributions summary:Nikita primarily contributed to the project by addressing configuration and setup issues, including fixing Docker-related problems and adjusting build processes. They enhanced the project's development workflow by adding a pre-hook for Python version checking and resolving Celery broker URL mismatches. Furthermore, they worked on code cleanup and refactoring by removing files associated with open-source conventions and removing code blocks when opting out of features. The user also made various documentation improvements.
Contributions:12 commits, 2 PRs, 8 pushes in 11 months
pythonmachine-learningsolversudokupuzzles
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Nikita Shupeyko - AI ML And Cloud Infrastructure Architect & DevOps at Toffee AI