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I'm an AI/CS enthusiast blending research with practical product delivery. I specialize in multi-agent AI, retrieval-augmented generation, and context-aware generation, building scalable AI architectures and end-to-end pipelines. I enjoy turning complex problems into robust, user-friendly solutions that teams can adopt quickly. In collaboration with cross-functional teams, I focus on clear communication, clean code, and fast iteration to drive impactful outcomes. I’m open to roles involving AI-driven optimization, automation, and engineering environments where I can apply ML/AI to real-world workflows and empower teammates with practical, scalable tooling.…I'm an AI/CS enthusiast blending research with practical product delivery. I specialize in multi-agent AI, retrieval-augmented generation, and context-aware generation, building scalable AI architectures and end-to-end pipelines. I enjoy turning complex problems into robust, user-friendly solutions that teams can adopt quickly. In collaboration with cross-functional teams, I focus on clear communication, clean code, and fast iteration to drive impactful outcomes. I’m open to roles involving AI-driven optimization, automation, and engineering environments where I can apply ML/AI to real-world workflows and empower teammates with practical, scalable tooling.

Danya Labasi

AI Engineer, Data Scientist, AI Developer, +2

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I'm an AI/CS enthusiast blending research with practical product delivery. I specialize in multi-agent AI, retrieval-augmented generation, and context-aware generation, building scalable AI architectures and end-to-end pipelines. I enjoy turning complex problems into robust, user-friendly solutions that teams can adopt quickly. In collaboration with cross-functional teams, I focus on clear communication, clean code, and fast iteration to drive impactful outcomes. I’m open to roles involving AI-driven optimization, automation, and engineering environments where I can apply ML/AI to real-world workflows and empower teammates with practical, scalable tooling.…I'm an AI/CS enthusiast blending research with practical product delivery. I specialize in multi-agent AI, retrieval-augmented generation, and context-aware generation, building scalable AI architectures and end-to-end pipelines. I enjoy turning complex problems into robust, user-friendly solutions that teams can adopt quickly. In collaboration with cross-functional teams, I focus on clear communication, clean code, and fast iteration to drive impactful outcomes. I’m open to roles involving AI-driven optimization, automation, and engineering environments where I can apply ML/AI to real-world workflows and empower teammates with practical, scalable tooling.

Available to hire

I’m an AI/CS enthusiast blending research with practical product delivery. I specialize in multi-agent AI, retrieval-augmented generation, and context-aware generation, building scalable AI architectures and end-to-end pipelines. I enjoy turning complex problems into robust, user-friendly solutions that teams can adopt quickly. In collaboration with cross-functional teams, I focus on clear communication, clean code, and fast iteration to drive impactful outcomes.

I’m open to roles involving AI-driven optimization, automation, and engineering environments where I can apply ML/AI to real-world workflows and empower teammates with practical, scalable tooling.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Intermediate

Intermediate

Language

Arabic

Intermediate

English

Advanced

Work Experience

AI Solutions Engineer (Intern) at National Bank of Fujairah

February 1, 2025 - September 8, 2025

Conversational AI with Retrieval-Augmented Generation (RAG) and Context-Aware Generation (CAG): developed RAG systems to allow staff to query internal policies; integrated CAG to reduce latency and improve accuracy for static banking content. Designed multi-agent architecture capable of processing large documents in parallel using specialized AI agents with final aggregation logic, leveraging semantic chunking and token-efficient overlaps. Built modular preprocessing and training pipelines using spaCy, scikit-learn, and Hugging Face Transformers for scalable experimentation. Achieved an F1 score of ~0.92 on conflict detection and 100% accuracy on neutral test cases, outperforming baselines. Document intelligence: built scalable calable parsing pipelines using LlamaParse, OCR engines, and NLP; integrated data extraction from PDFs, images, and bilingual (Arabic–English) content, including non-OCR documents. Platform integration & support: managed UAT, VPN, and API integration tasks acr