AI Systems Engineering · RAG · Computer Vision · Evaluation

Building reliable, evidence-grounded AI systems.

I design, build, and evaluate AI systems across retrieval, computer vision, language, and decision-support workflows, with an emphasis on clarity, reliability, and practical use.

Selected work

Projects that show how I approach AI systems.

A selection of work across RAG, computer vision, model evaluation, and practical software workflows. Each case study explains the problem, implementation choices, results, and limitations.

How I work

A systems perspective from problem definition to evaluation.

My Information Systems foundation keeps the focus on users, data flow, maintainability, and decisions. My AI work adds modeling, experimentation, implementation, and structured evaluation.

AI systems and RAGRetrieval, grounded generation, citations, workflow design, and evaluation.
Computer visionClassification, detection, transfer learning, robustness, and practical visual workflows.
Model evaluationBaselines, model comparison, error analysis, suitable metrics, and clearly stated limits.
Decision-support designInterfaces and outputs structured around practical users and reviewable decisions.
Background

Information Systems foundation. Advanced AI specialization.

Professional Master in AI

King Abdulaziz University, 2026. Advanced study in machine learning, intelligent systems, and applied AI.

Bachelor in Information Systems

King Khalid University, 2020. Foundation in systems analysis, databases, and organizational workflows.

Project portfolio

Work spanning RAG, computer vision, language systems, security analytics, generative AI, and data modeling.

Open to opportunities

Looking for an AI engineer who can connect models, systems, and practical use?

I am interested in full-time roles and technical collaboration in AI systems, applied machine learning, RAG, computer vision, and model evaluation.