I build production-oriented software systems that combine AI/ML with backend engineering, distributed processing, and automation.

Currently focused on building systems around LLM applications, RAG pipelines, AI agents, APIs, databases, and scalable backend infrastructure.

AI Applications
     │
     ├── RAG & Knowledge Systems
     ├── AI Agents & Automation
     ├── LLM-powered Applications
     └── AI Developer Tools

Backend Systems
     │
     ├── REST APIs
     ├── Async Job Processing
     ├── Distributed Workers
     ├── Databases & Caching
     └── Real-time Systems

Engineering
     │
     ├── Docker & CI/CD
     ├── System Design
     ├── Testing & Observability
     └── Cloud-ready Architecture

Currently exploring: LLM applications · RAG · AI Agents · Embeddings · Vector Search · ML Engineering · Quantitative Systems

Next.js · Express · BullMQ · Redis · Qdrant · Gemini

A document intelligence system that processes PDFs asynchronously and enables semantic question answering over uploaded knowledge.

Engineering focus:

• Asynchronous PDF processing
• Queue-based worker architecture
• Embedding generation
• Vector search with Qdrant
• LLM-powered answer generation
• Job status & progress tracking
• Source-grounded responses
• Scalable document ingestion

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Next.js · Express · Gemini · Tavily · PostgreSQL · Prisma

AI-powered search application combining web retrieval with LLM-based response generation.

Engineering focus:

• Web search + LLM pipeline
• Streaming AI responses
• Conversation persistence
• PostgreSQL data modeling
• Authentication
• API architecture
• Dynamic conversation routing

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React · Express · Gemini · TypeScript

An AI-powered developer tool that analyzes source code and generates contextual explanations.

Engineering focus:

• LLM API integration
• Structured API design
• Rate limiting
• Input validation
• Security middleware
• React state management
• Developer-focused UX

🔗 View Repository

I'm particularly interested in the intersection of:

          Artificial Intelligence
                   │
                   ▼
        ┌────────────────────┐
        │   AI Applications  │
        └─────────┬──────────┘
                  │
       ┌──────────┼──────────┐
       ▼          ▼          ▼
      RAG       Agents      ML
       │          │          │
       └──────────┼──────────┘
                  ▼
          Backend Systems
                  │
       ┌──────────┼──────────┐
       ▼          ▼          ▼
   Databases    Queues      APIs
       │          │          │
       └──────────┼──────────┘
                  ▼
        Production Systems

Areas I'm actively exploring:

• AI/ML Engineering
• LLM Systems
• Retrieval-Augmented Generation
• Agentic Systems
• Backend & Distributed Systems
• System Design
• Automation
• Quantitative & Data-Driven Systems
• Cloud & DevOps

Advanced Backend Architecture
        ↓
Distributed Systems
        ↓
AI / ML Engineering
        ↓
LLM & Agent Architectures
        ↓
Production Deployment
        ↓
System Design

I prefer learning by building systems rather than only following tutorials.

Build → Measure → Debug → Optimize → Deploy

I try to understand not only how to use a technology, but also:

• Why it exists
• What problem it solves
• How it works internally
• Where it fails
• How it scales
• How it behaves in production

I'm interested in collaborating on:

• AI/ML projects
• Backend systems
• Open-source projects
• Developer tools
• Automation platforms
• Research-oriented engineering projects