I bridge the critical gap between Raw LLM Capabilities and Robust Production Systems.
My passion lies at the intersection of High-Performance Infrastructure (SRE) and Applied AI. I don't just write code; I architect scalable, cloud-native platforms where intelligent systems live—transitioning from simple API wrappers to complex architectures and orchestrations on
Kubernetes.
I focus on building systems that are reliable, observable, and scalable.
| Domain | Technologies & Tools |
|---|---|
| 🧠 Languages | Python, Dart, TypeScript |
| ☁️ Cloud & SRE | AWS, Kubernetes, Docker, Terraform, Cloudflare |
| 🛠️ AI & Data | LangGraph, QDrant, MemGraph |
| 📊 Tools | VictoriaMetrics, Grafana, Git, Linux, FastAPI |
My primary goal is deepening my expertise in Cloud-Native AI Architecture:
- Agentic Workflows: Building stateful, memory-aware AI agents using LangGraph and Mem0.
- Infrastructure as Code: Automating scalable deployments using Terraform on AWS.
A selection of my work focusing on system architecture, IoT, and AI pipelines:
Click to expand and see project details
-
The Riber: Multi-Modal Edge AI Orchestration Engine (Prototype / In Development)
- Description: A self-hosted, privacy-first AI agent framework replacing SaaS dependencies. Orchestrates a Stateful Multi-Agent System using LangGraph with <500ms audio-to-audio latency.
- Stack:
LangGraph,Memgraph,LlamaIndex,Qdrant,Mem0,Docker,FastAPI,Gemini 2.5 Live. - Note: This project is currently a private repository focusing on advanced R&D.
-
HotelMind: AWS IoT & Hardware System (Teknofest 3rd Place)
- Description: An award-winning system that facilitates remote management of hotel rooms through an AI-supported IoT infrastructure.
- Architecture: Built on AWS IoT Core using MQTT for real-time bidirectional communication between mobile apps and edge devices.
- Stack:
AWS(IoT Core, Lambda, DynamoDB),Flutter,Raspberry Pi,MQTT. - Achievement: Secured a top-three finish in a highly competitive national technology competition.
- The project code source will be available soon.
-
- Description: Designed and built a modern, fast, and reliable microservices system ready for Kubernetes deployment.
- Technologies:
Cloudflare(Workers, Tunnels),Docker,Traefik(Load Balancer),Flutter,GraphQL,FastAPI,RabbitMQ,Couchbase,VictoriaMetrics&Grafana. - Note: This project is a proprietary, full-stack implementation showcasing modern DevOps and backend principles.
-
- Description: An intelligent application for analyzing and categorizing invoices, currently under development.
- Technologies:
Flutter,Google ML Kit,Gemini API,Firebase.
-
- Description: Developed an artificial intelligence and visual position estimation algorithm to control drone landing, identifying safe zones and obstacles.
- Technologies:
Python,OpenCV,YOLO, Computer Vision Libraries. - Achievement: Recognized as a finalist for its innovative approach to autonomous control.
- The project code source will be available soon.
- Medium articles about the project where I fixed are problems.
-
- Description: Engineered functional embedded software for a satellite payload. The system managed data telemetry, parachute deployment, and live video transmission with a command-based color filter.
- Technologies:
STM32 F401 (FreeRTOS),Raspberry Pi(Zero W & Camera),LoRa,TS/RS822,Servo Motors, Sensors (BMP280,MPU9250). - Note: This project involved complex hardware-software integration under challenging constraints.
- The project code source will be available soon.
GitHub Statistics
