Open to opportunities

Abdurrahman Khan

@abdurrahmankhan1

Message

Generative AI engineer focused on LLMs, RAG systems, and multimodal solutions.

Pakistan

Message

What I'm looking for

I am seeking roles building LLM-driven and multimodal AI systems where I can apply model fine-tuning, RAG engineering, and scalable deployment while continuing research and responsible AI development.

I am a Computer Science student and Generative AI engineer focused on building LLM-driven and multimodal RAG systems, fine-tuning models (LoRA/PEFT), and developing retrieval-based generation pipelines. I have practical experience with embeddings, vector databases, prompt engineering, model optimization, and responsible AI practices.

My projects include multimodal student engagement analysis, an LLM & RAG–powered personalized learning system, and a multimodal RAG query system that extracts text and images from PDFs. I leverage PyTorch, TensorFlow, transformer architectures, CLIP/Sentence-BERT embeddings, and production-oriented tools to deliver source-grounded, low-latency solutions.

Experience

Work history, roles, and key accomplishments

Current

Student Researcher

Current

FAST University Islamabad

Aug 2022 - Present (3 years 6 months)

Pursuing Bachelor's in Computer Science with a final-year project on AI-powered multimodal student engagement analysis combining CV and LLM components to provide actionable classroom insights.

Computer Vision Transformers PyTorch OpenCV Deep Learning

GenAI Engineer

Self Employed

Developed multimodal Generative AI and RAG systems, including LLM fine-tuning (LoRA/PEFT) and retrieval pipelines to produce source-grounded, low-latency responses for educational and product-search applications.

Generative AI Embeddings Vector Databases Prompt Engineering PyTorch TensorFlow Python

Education

Degrees, certifications, and relevant coursework

FAST National University of Computer and Emerging Sciences, Islamabad

Bachelor in Computer Science, Computer Science

2022 -

Pursuing a Bachelor in Computer Science with focus on Generative AI, LLMs, and RAG systems; practical experience in embeddings, vector databases, and retrieval-based generation pipelines.