Building LLM-powered applications, knowledge graphs, and intelligent automation systems
I am an AI Application Engineer specializing in building real-world AI systems powered by large language models, knowledge graphs, and data-driven pipelines.
My experience spans e-commerce AI applications, including knowledge graph construction with Neo4j, LLM-enhanced recommendation systems, and automated content generation tools for product publishing. I focus on turning complex business requirements into scalable AI solutions by integrating structured data, retrieval systems, and LLM-based reasoning.
I have hands-on experience with RAG pipelines, agent-based workflows, prompt engineering, and data processing using Python, MySQL, and Pandas. I enjoy building systems that are not just technically sound, but also practical and directly usable in production environments.
Currently, I am focused on AI application development, especially in areas like intelligent recommendation systems, knowledge graph integration, and LLM-powered automation tools.
Work Terms
- I work on clearly defined tasks or well-scoped project requirements.
- All deliverables will be implemented in Python-based AI/ML stacks unless otherwise agreed.
- I prefer milestone-based collaboration for larger projects.
- Communication is expected to be clear and structured to ensure efficient execution.
- I provide updates regularly during development and am open to iterative feedback.
- Source code and documentation will be delivered upon completion of each milestone.
- I do not take on vague or undefined requirements without initial clarification.