Available for new opportunities

 

Building
Intelligent
Systems With AI.

Bachelor of Engineering in Information Technology graduate specializing in AI Engineering and Backend Engineering.

Explore my workLet's connect

Sumeet's AI engineering stack

AI ENGINE

Building intelligent systems

RAG

Retrieve → Rerank → Generate

LLMs

Reasoning and language intelligence

Agents

Tool-using autonomous workflows

Vector DB

Semantic search and knowledge retrieval

React

Interactive AI application interfaces

FastAPI

High-performance AI backend APIs

01 /about_core

Building intelligent systems with purpose & precision.

profile_core.json

Sumeet Sonar

AI & Backend Engineer

<status>
Available for contract & full-time roles
<focus>
LLMs, Agentic RAG & Backend APIs
<degree>
B.E. Information Technology (CGPA: 7.63)

Dedicated Information Technology graduate with a strong passion for designing and building context-aware intelligence cores, scalable backend services, and clean front-end application architectures.

sys_init // boot_successsecure_run
The paradigm

Bridging Software Cores & Intelligent Models

As a Bachelor of Engineering in IT graduate, I bridge the gap between software backends and intelligent models. I build scalable full-stack applications with FastAPI, Django, and React, integrating structured semantic searches with ChromaDB, orchestration frameworks like LangChain and LangGraph, and multi-provider LLM routing (OpenAI, Gemini, Groq, Ollama, Hugging Face).

My hands-on experience spans machine learning pipelines, NLP data workflows, token caching, WebSockets telemetry, Solidity smart contract verification, and role-based access control (RBAC). I focus on building reliable, grounded systems that solve actual domain problems.

Practical AI integration

I focus on building grounded pipelines that keep AI output accurate, cost-effective, and fully integrated into core application backends rather than isolated templates.

03 /capabilities_core

What I Can Build

capability_logger // inspectorengaged

statement / AI & Machine Learning

“Developing robust machine learning pipelines, data preprocessing, and model evaluations.”

// core capabilities

  • Data preprocessing, cleaning, feature engineering, and exploratory data analysis (EDA)
  • Classification & regression pipeline implementation using Scikit-learn and XGBoost
  • Model testing, debugging, and metrics evaluation (F1, ROC/AUC, accuracy)

technology stack

PythonScikit-learnXGBoostStreamlitNLPPandasNumPy

related deployment

Smart AI Resume Analyzer with Blockchain Certificate Verification
core_run
04 /tech_universe

My Technology Ecosystem

constellation // languages8 nodes

Languages

  • Python
  • Java
  • SQL
  • JavaScript
  • TypeScript
  • HTML
  • CSS
  • Solidity

rotate the ecosystem — select any constellation to inspect its stack

Languages

  • Python
  • Java
  • SQL
  • JavaScript
  • TypeScript
  • HTML
  • CSS
  • Solidity

AI & GenAI

  • Machine Learning
  • NLP
  • LLMs
  • RAG
  • LangChain
  • LangGraph
  • Prompt Engineering
  • Semantic Search
  • ChromaDB
  • Multi-provider LLM Integration
  • Sentence Transformers

Backend Systems

  • FastAPI
  • Django
  • Async APIs
  • REST APIs
  • SQLAlchemy
  • Alembic
  • WebSockets
  • JWT
  • RBAC

Frontend & Web3

  • React
  • Vite
  • Streamlit
  • Web3.js
  • Solidity Smart Contracts

ML & Data Sci

  • Scikit-learn
  • XGBoost
  • Pandas
  • NumPy
  • Feature Engineering
  • Model Evaluation
  • EDA

Databases

  • PostgreSQL
  • MySQL
  • Oracle SQL

DevOps & Tools

  • Git
  • GitHub
  • Docker
  • Docker Compose
  • GitHub Actions
  • Railway
  • Nginx
  • Jupyter Notebook
  • Power BI

LLM Integration

  • OpenAI
  • Gemini
  • Groq
  • Hugging Face
  • Ollama
05 /portfolio_index

Featured Projects

case_study // project_01log

AI Clinical Copilot & Healthcare Platform

IntelliICU

Real-time clinical decision support platform leveraging active WebSocket telemetries and RAG clinical queries.

// key technical features

  • Engineered an AI-powered clinical decision support system using FastAPI, LangChain, ChromaDB, and Retrieval-Augmented Generation (RAG).
  • Architected a configurable multi-provider LLM integration layer supporting OpenAI, Gemini, Ollama, and Hugging Face models.
  • Secured the platform with JWT Authentication and RBAC, added WebSockets for real-time updates, and deployed async FastAPI endpoints on Railway.

technology stack

ReactFastAPIPostgreSQLLangChainChromaDBWebSocketsDockerJWTRailway
Repo
06 /career_log

Experience & Credentials

A record of the practical experience, education, and credentials shaping my path as an AI and software engineer.

record_view // exp_logVERIFIED

Data Science Intern

CodSoft // Apr 2025 — May 2025

// inspection_report: Raw Data Processing & EDA

Applied Machine Learning and NLP techniques to real-world datasets using Python and Scikit-learn. Converted raw transaction files and document lists into normalized records, handling missing entries, outliers, and feature encoding pipelines.

data › processing › model › evaluation core_run
01 / source_codeactive_repos

GitHub & Open Source

Explore the systems behind my work. View codebases, multi-agent frameworks, and vector ingestion layers.

Explore My Code
02 / engineering_profileportable_doc

Offline Resume

Download my complete engineering profile. Access a structured copy detailing skills, qualifications, and deployments.

Download PDF Resume
07 /open_channel

Let's build something intelligent together.

I'm open to discussing backend engineering roles, GenAI research integrations, full-stack applications, or custom machine learning pipelines.

status: available_for_opportunities

focus: ai systems / backend / rag

location: Navi Mumbai, India

phone: +91 8624880655

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