I'm a Computer Science Engineer and AI-focused developer passionate about building intelligent, scalable, and production-ready applications.

I enjoy working at the intersection of Backend Engineering, Generative AI, RAG, AI Agents, and Cloud Technologies, turning complex problems into practical software solutions.

• 🤖 Exploring Generative AI, LLMs, RAG, and Agentic AI
• 🧠 Building AI Agents and intelligent backend systems
• 🔗 Working with LangChain and LangGraph for AI orchestration
• 📚 Learning and implementing RAG pipelines with vector databases
• 🛡️ Exploring LLM Evaluation, AI Guardrails, AI Security, and LLM Gateways
• ⚙️ Experienced in developing REST APIs and backend services
• 🐍 Strong experience with Python, FastAPI, Django, and asynchronous processing
• ☕ Building backend applications using Java and Spring Boot
• 🌐 Experienced with React, Node.js, Express, and modern web technologies
• ☁️ Exploring AI deployment, cloud infrastructure, Docker, and CI/CD
• 🔍 Interested in Open Source contribution and developer tooling

I'm currently focused on building production-oriented AI applications and understanding the complete AI engineering lifecycle.

• Large Language Models (LLMs)
• Prompt Engineering
• Function / Tool Calling
• Structured Outputs
• LLM APIs
• Conversation Memory
• Streaming LLM Responses

• Document ingestion
• Chunking strategies
• Embeddings
• Semantic Search
• Vector Databases
• pgvector
• Supabase Vector
• Retrieval pipelines
• Context-aware generation

• AI Agents
• Agent Architecture
• Tool Calling
• Agent Memory
• Multi-Agent Systems
• Agent Orchestration
• LangChain
• LangGraph
• MCP (Model Context Protocol)

• LLM Evaluation
• RAG Evaluation
• AI Guardrails
• Prompt Injection Testing
• LLM Security
• AI Gateways
• AI Observability
• Agent Evaluation

An AI-powered metro assistant designed to help users with:

• 🚉 Metro station discovery
• 🗺️ Source → destination route planning
• 📍 Location-based nearest station detection
• 🔄 Interchange detection
• 💰 Fare and travel guidance
• 🤖 LLM-powered journey explanations
• 💬 Conversational AI interface

Architecture: User → AI Agent → Tools → Metro Data → Route Engine → LLM → Response

Generative AI
      ↓
LLMs & Prompt Engineering
      ↓
RAG & Vector Databases
      ↓
Tool Calling
      ↓
AI Agents
      ↓
LangChain
      ↓
LangGraph
      ↓
MCP
      ↓
Multi-Agent Systems
      ↓
LLM / RAG Evaluation
      ↓
AI Guardrails & Security
      ↓
AI Deployment & Observability

I'm actively interested in contributing to open-source projects, particularly in:

• 🤖 AI / GenAI
• 🔗 RAG
• 🧠 Agentic AI
• 🐍 Python
• ☕ Java / Spring Boot
• ⚡ Backend Engineering
• 🛠️ Developer Tools

I believe the best way to improve as an engineer is to build, contribute, review, and learn from real-world codebases.

I'm always interested in connecting with developers, AI engineers, open-source contributors, and people building interesting products.

LinkedIn: https://www.linkedin.com/in/vaibhavmashal/

LeetCode: https://leetcode.com/u/Vaibhav_Mashal/

Email: vaibhavmashal098@gmail.com