R&D Engineer · AI Systems & Distributed Infrastructure
I build things that ship — from fine-tuning LLMs and orchestrating Multi-Agent Systems to deploying production pipelines on Kubernetes. Currently pursuing an MSc in Computer & Systems Engineering at Alexandria University while working at AIC.
- Multi-Agent translation system — orchestrating specialized agents (translation, QA, refinement, consistency) with RAG context enrichment, deployed on on-premises K8s
- LLM fine-tuning — SFT and RL alignment for domain-specific literary translation
- Computer Vision pipelines — satellite imagery segmentation (92% accuracy, 90% inference time reduction) and crop classification at scale
- MVCC internals (at ITTIA DB) — novel concurrency technique optimized for constrained IoT databases
AI / ML
Backend & Infrastructure
Infra & Data
| Project | Description | Stack |
|---|---|---|
| Book Translation MAS | Multi-agent orchestration system for automated literary translation with RAG and quality checking | Python, LangChain, K8s, vLLM |
| Satellite CV Pipeline | Crop classification and building detection on satellite imagery — 92% accuracy, 90% faster inference | PyTorch, OpenCV, Triton |
| Unilever CRM Platform | Dual enterprise CRM with AI chatbot, real-time chat, and full Azure cloud deployment | Spring Boot, Angular, Azure, CI/CD |
| ITTIA DB Benchmarks | MVCC concurrency research and benchmark suite for embedded IoT databases | C/C++ |
| PintOS | Extended OS kernel with advanced scheduling, virtual memory, and file system | C |
