> init agent_agentic_system...
> loading langgraph_agent_twin.db... OK
> establishing neural_link... SECURE
> rendering tanuj_rajput_portfolio...
Open for Internships & Projects

Building AI Agents That Solve Real Problems.

I'm Tanuj Rajput, a third-year Computer Science student specializing in AI Agents, LangGraph workflows, RAG systems, FastAPI backends, and intelligent automation.

Tanuj.py
Futuristic Developer AI Workspace Layout Graph Visualization
About Me

I enjoy turning LLMs into useful products.

Over the past year, I've focused heavily on building AI systems using LangChain, LangGraph, FastAPI, and modern AI infrastructure.

Rather than simple chatbot templates, I enjoy building production-grade autonomous workflows, semantic retrieval pipelines, and intelligent multi-agent architectures that process complex tasks end-to-end.

Agent Architectures

Building cyclic graph-based agents that self-correct, plan, and execute using LangGraph.

FastAPI & Python

Writing high-performance backend microservices and automation APIs with full type safety.

Semantic Storage

Integrating vector databases (Pinecone, Chroma, Qdrant) with advanced RAG systems.

Production Ready

Debugging nodes and tracking executions with LangSmith to resolve production bottlenecks.

Experience

Work Experience

My professional internships developing production conversational flows and automated AI agents.

AI Automation and Chatbot Development Intern

May 2026 - Present · 2 mos
Saral One · Internship Bhopal, Madhya Pradesh, India (Remote)
  • Building a WhatsApp AI Lead Qualification System to automate lead engagement and qualification workflows.
  • Developing conversational AI flows to capture, score, and route leads based on user responses.
WhatsApp API FastAPI LangChain MongoDB

AI Developer Intern

Dec 2025 - Mar 2026 · 4 mos
Metry AI · Internship Taipei City, Taiwan (Remote)
  • Developed AI-powered appointment booking chatbots for salon and beauty SMBs.
  • Implemented conversational flows to handle new bookings, cancellations, rescheduling, and general user queries.
  • Designed structured dialogue logic and state management for multi-step booking workflows.
FastAPI LangGraph LangChain State Management
Stack

Technical Expertise

Practical technologies I use to build robust, automated systems and intelligent backends.

AI & Agents

LangChain LangGraph CrewAI RAG Prompt Eng. AI Agents LangSmith MCP

Backend

FastAPI Django Python REST APIs JSON Schema Uvicorn

Machine Learning

PyTorch Scikit-learn Pandas NumPy Transformers

Databases

MongoDB MySQL Vector DBs Redis Cache

DevOps

Docker Redis Kubernetes AWS (Learning)

Tools

Git Streamlit n8n Jupyter Postman
Projects

Featured Work

Production-grade AI solutions and integrations designed for real business tasks.

AI Research Agent Screenshot showing agent nodes dashboard

AI Research Agent

An autonomous multi-agent research assistant built using LangGraph. The agent plans, crawls the web, critiques drafts, and compiles complete formatted reports with citations.

LangGraph LangChain FastAPI LangSmith MongoDB
WhatsApp lead qualification dashboard interface screenshot

WhatsApp AI Lead Qualifier

A high-scale WhatsApp automation system built on FastAPI. It engages users with natural language, validates lead qualification criteria using custom constraints, and stores verified records.

FastAPI LangChain WhatsApp API MongoDB
RAG Question Answering system PDF search visualization screenshot

RAG Question Answering System

A retrieval-augmented generation engine that accepts large PDFs and docx files. Performs intelligent layout chunking, vector index mapping, and handles multi-turn question answering.

LangChain FastAPI Vector DB Docker
Product semantic recommendation analytics interface screenshot

AI-Powered Gadget Recommender

An intent-based recommendation engine that utilizes sentence embeddings to match user queries with inventory catalog matches. Provides low-latency recommendation mappings.

LangGraph PyTorch FastAPI Pandas Vector DB
Growth

Learning Journey

Timeline tracing the technical milestones I've crossed as a Computer Science student.

Phase 1

Learning Python

Mastered core object-oriented structures, algorithms, and logical foundations.

Phase 2

Machine Learning Foundations

Explored model architectures, data analysis (Pandas/NumPy), and Scikit-Learn pipelines.

Phase 3

FastAPI Backend Development

Learned async routing, REST schemas, server optimizations, and microservice structures.

Phase 4

LangChain Framework

Integrated prompt templates, retrieval mechanisms, chains, and conversational memory structures.

Phase 5

LangGraph Agent Architectures

Engineered complex, cyclic graph-based agents that self-correct and execute multi-step workflows.

Phase 6

Docker Containers

Configured multi-container microservices to isolate environments and standardize deployments.

Phase 7

LangSmith Tracing

Monitored prompt sequences, latency profiles, and intermediate node outputs to debug agent workflows.

Phase 8

Redis Caching

Configured memory caches and message brokers to accelerate session states and webhook queues.

Phase 9

Kubernetes Cluster Setup

Began orchestrating containers, load balancing node systems, and handling scale routing.

Phase 10

MCP Servers Integration

Connecting LLMs with custom external APIs and local environments securely using the Model Context Protocol.

Value

Why Work With Me

Practical value I bring to developers, startups, and product teams.

AI Agent Development

Designing self-correcting workflows, tool usage graphs, and task planners rather than basic prompting.

LLM Integration

Integrating vector databases, layout chunking RAG systems, and semantic queries efficiently.

Backend APIs

Writing clean, typed, high-performance async backends with FastAPI to serve production requests.

Automation Systems

Connecting APIs, background jobs, webhooks, and tools like n8n/Redis to automate manual processes.

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LeetCode Solved
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AI Projects Built
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AI Tech Mastered
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AI System Deployments
Mindset

Core Philosophy

What drives my coding approach and engineering decisions daily.

"Focused on building practical, production-ready AI products rather than simple chatbot templates."

TR
Tanuj Rajput Engineering Mindset

"Always learning modern AI technologies, containerization, and tracing pipelines to build reliable software."

AL
Continuous Learning Tech Growth Target

"Interested in solving real business problems and optimizing manual workflows using agentic automation."

PM
Problem Solving Practical Impact

Let's build something intelligent together.

I am currently open to internships, freelance projects, and AI agent development integrations. Get in touch and let's coordinate!

Availability Status

  • Open for AI Internships
  • Freelance Projects
  • AI Agent Integrations
Download Resume
Tanuj's AI Twin Active Agent