I'm a Full Stack Developer and AI Engineer focused on building enterprise applications and AI-powered systems.
I combine strong software engineering foundations with hands-on experience in Generative AI, LLM applications, RAG, AI Agents, semantic search, tool calling, and modern AI architectures.
My goal is to build practical systems where software engineering and AI work together to solve real-world problems.
My current focus is building practical AI systems using:
- LLMs & Generative AI
- RAG (Retrieval-Augmented Generation)
- AI Agents & Agentic Workflows
- LangChain & LangGraph
- LlamaIndex
- Model Context Protocol (MCP)
- Function Calling & Tool Calling
- Embeddings & Semantic Search
- Vector Search & Vector Stores
- Human-in-the-Loop
- AI-powered Automation
- LLM Application Architecture
Python · FastAPI · LangChain · LangGraph · LlamaIndex · Gemini · Cohere · MCP · Firecrawl · Playwright
I have professional experience developing and maintaining enterprise-scale applications, working across frontend, backend, databases, APIs, and business logic.
Angular · TypeScript · JavaScript · React · Next.js · HTML · CSS
C# · .NET · ASP.NET Core · Python · FastAPI · REST APIs · Microservices
Oracle · SQL Server · PostgreSQL · MongoDB · SQL
Git · GitHub · Azure DevOps · Docker · AWS · CI/CD
A full AI-powered research application combining LLMs, RAG, AI Agents, tools, and external data sources.
Explore the AI Engineer Repository →
Python · FastAPI · LangChain · Gemini · Cohere · RAG · Vector Search · Firecrawl
- LLM-powered Research Assistant
- RAG & Semantic Search
- AI Agent & Agentic Workflows
- Tool Calling
- Web Search & Data Extraction
- Human-in-the-Loop
- Source Management
- Grounded Responses & Citations
- AI-generated Artifacts
- Embeddings & Vector Retrieval
The project demonstrates how an LLM can be connected to knowledge sources, retrieval systems, external tools, and application logic to create a complete AI-powered application.
A full-stack enterprise application demonstrating end-to-end software development across frontend, backend, APIs, business logic, and data access.
Explore the Full Stack Enterprise App →
Angular · TypeScript · C# · .NET · REST APIs · SQL
- Angular frontend
- C# / .NET backend
- REST API integration
- Database-driven application
- Business logic & services
- Enterprise application architecture
- Frontend–Backend integration
- CRUD & data management
The project demonstrates my ability to develop complete applications across the stack — from user interfaces and APIs to backend services and data access.
I'm particularly interested in building systems where:
LLMs + Agents + Tools + RAG + APIs + Real Data
come together to solve real-world problems.
I'm continuously exploring new approaches in:
- AI Engineering
- Agentic AI
- Generative AI
- Advanced RAG
- LLM Application Architecture
- AI + Full Stack Development
I believe the most useful AI applications are not just models — they are complete software systems.
My focus is on connecting:
Models → Retrieval → Tools → APIs → Data → Business Logic
to build AI applications that are practical, maintainable, and scalable.
Python · C# · Java · TypeScript · JavaScript · SQL
React · Next.js · Node.js · Ionic · Entity Framework Core · Microservices
Azure DevOps · AWS · Docker · Git · GitHub · CI/CD
- GitHub: @shani01846
- LinkedIn: Shani Kirzon
Building reliable software and intelligent systems.