🚀 AI Systems & LLM Backend Engineer
Building scalable AI architectures, production-ready agent systems, and high-performance backend infrastructures.
I specialize in designing and engineering robust AI-powered systems — from Retrieval-Augmented Generation (RAG) pipelines to advanced LLM orchestration and distributed backend architectures.
- 🤖 Designing AI Agent Architectures (tool-calling, multi-agent workflows, orchestration)
- 🔎 Building Production-Grade RAG Pipelines (vector search, hybrid retrieval, reranking)
- ⚡ LLM Infrastructure (vLLM, inference optimization, prompt engineering)
- 🏗️ Scalable Backend Systems for AI applications
- 🔬 Experimenting with fine-tuning strategies & model optimization
I focus on understanding systems at a fundamental level — because once the core mechanics are clear, you can build anything on top of them.
Python • LangChain • LLM APIs • RAG • Agents • Vector Databases • Embeddings • vLLM • Prompt Engineering
Node.js • NestJS • Express • TypeScript • REST APIs • Kafka • Docker • AWS • Microservices
MongoDB • PostgreSQL • Cloud Basics (AWS) • GitHub Actions
React (MERN) – Building UI layers for AI-powered applications
- AI-powered backend systems
- Agent-driven automation workflows
- Scalable APIs for LLM-based products
- Full-stack AI applications
- Clean, understandable educational AI implementations
- Advanced Agent Orchestration
- Streaming LLM systems
- High-performance inference optimization
- Distributed AI architectures