SYSTEM.KERNEL :: v2.5.0 ONLINE

Hello, I'm
Nithin Chakravarthi

Software Engineer focused on scalable, production-grade applications and real-time embedded systems, with experience in AI infrastructure.

LOADED_MODULES:
PYTHON JAVA NODE.JS TENSORFLOW EMBEDDED AWS
portfolio.tsx


    
# About.system
Nithin
OPERATOR
NITHIN CHAKRAVARTHI
ROLE
SYSTEMS_ENGINEER
LOCATION
Cincinnati, USA
STATUS
OPEN
>_ user_profile.log
→ whoami
Software Engineer focused on distributed platforms, real-time embedded systems, and AI infrastructure engineering.
→ cat mission.txt
Building intelligent automation systems integrating AI, distributed systems, and scalable backend engineering. Focused on production-ready AI solutions.

certifications.registry

# Skills.json
🌐 Drag to explore skills universe
$ git log --stat --oneline
c0mm1t1 HEAD → ai-ml Mobius Networks

AI / ML Intern @ Mobius Networks

Worked on Agent Orchestration Framework for automating business workflows using AI agents. Built data pipelines, ML integrations and contributed to low-code AI platform development.

Python FastAPI LangChain Flowise LLM Agents Gen AI RAG Node.js Docker REST APIs Git
📅 2024-25
c0mm1t0 HEAD → research IERDC

Research Intern @ Interdisciplinary Research & Development Cell

Worked on real-time interdisciplinary R&D across Embedded, IoT, AI/ML, and full-stack technologies, developing integrated hardware–software solutions.

ESP32 Embedded C Python Java React Node.js WebSockets AI/ML IoT Systems Hardware Design PCB Concepts System Integration
📅 2021-23
⚬ Initial Commit (Engineering Journey Started 🚀)
$ ls -la ~/projects

PINNED PROJECTS

Wireless real-time public addressing platform using ESP32 speaker nodes and WebSocket-based broadcasting backend replacing traditional amplifier infrastructure.

ESP32 Node.js WebSockets IoT

AI middleware orchestration framework enabling prompt-driven creation and coordination of multi-agent workflows built over Flowise architecture.

Python FastAPI LLMs Agents

Hybrid multi-retriever LLM orchestration system improving conversational memory recall and semantic context retrieval beyond static vector baselines.

Python RAG Embeddings LangChain
$ ./contact.exe
contact_info.json
1{
2"status": "open_to_work",
4"socials": {
5"github": "@bnithin0605",
6"linkedin": "@bnithin0605",
7"instagram": "@nithin.explains"
8},
9"location": "Ohio, USA"
10}
11// Waiting for connection...
TS sendMessage.ts ×
// Run this script to send a message
const send = async () => {
const name = "";
const email = "";
await api. submit ({
name, email,
message:
});
}