Building intelligent systems with LLMs and RAG. I focus on real-world applications, not demos.
Built an intelligent agent that combines reasoning, retrieval, and action. Uses LLMs for decision-making with RAG-backed knowledge retrieval for accurate responses.
End-to-end RAG system with embeddings, vector storage, and evaluation framework. Integrated with PostgreSQL for semantic search and grounding of AI responses.
Scalable notification service using event-driven architecture. Built with TypeScript, handles real-time notifications with fault tolerance and retry mechanisms.
Computer vision + AI system to assist visually impaired users. Integrates real-time image processing with natural language descriptions using advanced models.
Built production-grade REST APIs with FastAPI. Includes authentication, rate limiting, async processing, and comprehensive API documentation.
Developed systematic approach to prompt engineering with evaluation metrics. Includes few-shot learning, chain-of-thought, and performance benchmarking.
I'm an AI/ML engineer with 2.5+ years of experience building production-grade systems. My focus is on LLMs, RAG systems, and intelligent agents that solve real problems in the field.
I specialize in designing RAG architectures with proper evaluation frameworks, building scalable backend systems, and creating AI agents that combine reasoning with reliable information retrieval. I believe in shipping real systems, not just proof-of-concepts.
When I'm not building AI systems, you'll find me contributing to open source, exploring new model architectures, or mentoring engineers interested in production ML systems.