Rhodes, Greece
© 2026 Papagrigoriou Vasileios Savvas
Backend Platforms and AI Systems Built to Run in Production
MSc in Artificial Intelligence · Aristotle University of Thessaloniki
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© 2026
Backend & API Engineering
REST APIs and services built for reliability, with clean boundaries and predictable data flow.
Data & ML Pipelines
Automated pipelines that turn large, messy datasets into inputs you can trust.
Infrastructure & Scale
Containerized services and CI/CD on AWS, tuned to stay fast as data and traffic grow.
Backend
I build REST APIs and backend services with clear integration boundaries and predictable data flow. The focus is on reliability under real traffic, clean contracts between systems, and performance that holds as usage grows.
Data / ML
I automate the path from raw data to usable inputs. Pipelines that handle large, messy datasets through parsing, validation, and transformation, so analysis and models run on data you can actually trust.
Platform
I containerize and deploy services with CI/CD on AWS. This keeps environments reproducible, releases predictable, and query performance tuned as data volume and traffic keep climbing.
Plus supporting work across databases, cloud infrastructure, and CI/CD.
The Story Behind My Work and the Experiences That Shaped My Craft
Biological Computation Lab
[Sep 2024 -July 2025]
Assistant Researcher
Developing computational tools and automating bioinformatics pipelines for complex biological and metagenomic data analysis
Boosted research productivity by 25% and cut processing times by 30%.
Business Optimal Software
[Feb 2024 - Present]
Full Stack Developer
Engineering mobile applications, optimizing relational databases, and deploying scalable backend services via Docker on AWS
Achieved 40% growth in app user engagement and improved database query times by 40%
Areas of Expertise
[MACHINE LEARNING & AI]
[Development & Automation]
[CLOUD & INFRASTRUCTURE]
I’m a backend and AI engineer with an MSc in Artificial Intelligence from the Aristotle University of Thessaloniki.
I build the systems that sit behind products — REST APIs, data pipelines, and containerized services on AWS — tuned so they stay fast as data grows. Recent work includes cutting query response times by 40% across five production databases and automating bioinformatics pipelines that process metagenomic data 30% faster.
The research side runs alongside the engineering: my MSc thesis, PhyloFlask, is an open-source platform for large-scale phylogenetic visualization, presented at the Hellenic Bioinformatics Conference in 2025.
Records managed
Faster query response
Faster data pipelines
My Work Speaks for Itself
From concept to execution
PhyloFlask Data Platforms
QuickFind Machine Learning
Open-Source Compliance Cockpit Web Experience
FeedClinic Data Platforms
myΠΕΑ Web Experience
Epiverse
SaaS Backoffice CRM Web Experience
GoFleet Web Experience
Horeca-Parts Web Experience
QuizMage for WooCommerce Web Experience
Essential Tools I Use
I use a refined set of design, development, and automation tools to build fast, scalable, and beautifully engineered digital experiences.
Python
AI & Backend Core
React
Frontend Development
PyTorch
Deep Learning
Docker
DevOps & Scaling
AWS
Cloud Infrastructure
PostgreSQL
Database Systems
FastAPI
Modern API Design
Stripe
Payment Processing
GitHub
Version Control
With 10+ Other Skills related to Design, Development
Reflections From
My Creative Journey
CI/CD and DevOps: How Reliable Software Actually Ships
by Jul 10, 2026
SQL vs NoSQL: Choosing the Right Database for Your Project
by Jul 10, 2026
APIs Explained: How Modern Software Connects Everything
by Jul 10, 2026Helpful Answers to
Your Common Questions
Do you implement Computer Vision for automated tasks?
Yes. I have hands-on experience in Computer Vision (CNNs, YOLOv5) for object detection, image processing, and automated visual content analysis.
Can you build automated data pipelines?
I develop automated bioinformatics and data pipelines that can cut processing times by 30% and significantly increase overall research or business productivity.
Do you work with Multi-Modal learning and Video analysis?
Yes. I have developed unsupervised models for multi-modal video summarization using visual and audio cues, utilizing advanced frameworks like PyTorch and TensorFlow.
Can you integrate AI chatbots or recommendation engines?
I build intelligent recommendation systems and AI-driven interfaces that learn from user behavior to provide personalized and relevant content.
How do you handle the deployment of ML models?
I deploy models as scalable microservices using Docker and AWS, ensuring that your AI features are reliable, fast, and easily maintainable.
How can Machine Learning benefit my business?
AI can automate complex data analysis, provide predictive insights, and personalize user experiences. I specialize in building ML models that solve specific operational bottlenecks.