I am a software engineer focused on applied AI, backend services, and automation. My work sits where models meet real product workflows: assistants that can act, RAG systems that retrieve the right context, APIs that are easy to integrate, and tools that remove repetitive work.
problem -> prototype -> evaluate -> harden -> ship -> improve| Current focus | AI agents, LLM pipelines, RAG, Go backend APIs, automations, developer tooling |
| Currently building | Uber Eats-style food delivery platform with a Go backend and product-grade service boundaries |
| Strongest stack | Python, Go, FastAPI, TypeScript, React, Node.js, PostgreSQL, Docker |
| Engineering bias | Small interfaces, practical architecture, measurable behavior, fast iteration |
| Notable signal | 2nd place, 2024 CS graduation projects, for a face-recognition attendance system |
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Local-first AI assistant for task execution, file operations, and development workflows.
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Startup idea for sovereign Arabic AI: building Arabic-first AI systems and training LLMs from the ground up.
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Open-source collaborator on a real-time global intelligence dashboard with 50k+ stars and 8k+ forks.
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Hospital workflow assistant concept with voice-to-text and automated form filling.
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Food delivery platform with customer, restaurant, ordering, and backend service workflows.
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Lightweight browser app for real-time score tracking in a custom card game.
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| Languages | Python, Go, Java, TypeScript, JavaScript, C |
| Backend | Go services, FastAPI, Node.js, REST APIs, service design, automation scripts |
| AI / ML | LLM apps, RAG, QLoRA, PyTorch, TensorFlow, practical ML workflows |
| Data / Infra | PostgreSQL, MongoDB, AWS, Docker, Linux, Git |
| B.S. Computer Science | Lebanese International University |
| Diploma, Software Engineering | Lebanese American University |
Open to building serious AI products, automation-heavy tools, and backend systems that actually get used.