Software Engineer · Vadodara, IN

Bhakti Darji — Software Engineer building full-stack products and AI-powered tools.

I build production-grade web applications with Angular and .NET, and I design AI systems — RAG pipelines, LLM-backed assistants — that solve real problems. Currently a Software Engineer Trainee at Rigel Networks, based in Vadodara, India.

View Projects →Download Résumé ↓Get in Touch →

zsh — whoami

$ whoami
bhakti.darji

$ cat role.json
{
  "title": "Software Engineer Trainee",
  "company": "Rigel Networks",
  "location": "Vadodara, IN",
  "focus": ["full-stack", "applied-ai"],
  "stack": {
    "web":   ["Angular 19", ".NET 9"],
    "data":  ["PostgreSQL", "Redis"],
    "ai":    ["LangChain", "RAG", "Pinecone"]
  }
}

$ _▍

01 / About

Engineer of two disciplines.

~1 yr experienceCGPA 8.92 / 10CSE (IoT)

I'm a software engineer with roughly a year of professional experience across full-stack development and applied AI. My day-to-day stack is Angular 19 and .NET 9, built on Clean Architecture, PostgreSQL, and Redis — but I'm equally comfortable in the AI/LLM side of engineering: LangChain, retrieval-augmented generation (RAG), Pinecone, and LLaMA.

I studied Computer Science & Engineering (IoT) at G H Patel College of Engineering & Technology, graduating with an 8.92 CGPA. What I care about most is building things that hold up under real use — not demos. My two flagship projects, an EHR system and an AI medical chatbot, reflect that: one is a full production-style healthcare platform with role-based access and measurable performance gains, the other is a retrieval-grounded AI assistant designed to give accurate, source-backed answers instead of confident guesses.

I'm currently exploring my next role at product and healthcare-tech companies, and longer-term, a Master's degree abroad.

02 / Selected Work

Case studies.

Two projects that reflect how I think about production systems.

01 · Full-Stack · Healthcare

EHR System

A full-stack Electronic Health Record system with role-based access, appointment scheduling, and PDF generation — built on Angular 19, .NET 9, PostgreSQL, and Redis. Cut API response times by ~40% through targeted caching.

Angular 19.NET 9Clean ArchitecturePostgreSQLRedisJWT/RBAC

Read case study →

02 · Applied AI · RAG

AI Medical Chatbot

A retrieval-augmented AI assistant for medical Q&A — built with LLaMA, LangChain, and Pinecone, served through a Flask API with Redis caching. Designed to ground answers in real source material instead of relying on the model's raw output.

LLaMALangChainPineconeRAGFlaskRedis

Read case study →

03 / Other Work

Also on the shelf.

Project 03

AI Transportation System

Real-time vehicle tracking platform with live dashboards and analytics.

Real-timeDashboardsAnalytics

Project 04

Sales Analytics Dashboard

Python/Pandas-based analytics tool with Power BI reporting and linear regression forecasting.

PythonPandasPower BI

Project 05

Object Detection System

TensorFlow-based computer vision project for real-time object detection.

TensorFlowComputer Vision

04 / Skills

Tools I reach for.

Frontend

Angular 19TypeScriptRxJSSignalsResponsive UI

Backend

.NET 9Clean ArchitectureREST APIsJWT/RBACEntity Framework Core

Data

PostgreSQLRedisSQL

AI / ML

LangChainRAG pipelinesPineconeLLaMAFlask

Other

Git/GitHubPython (Pandas, TensorFlow)Power BI

05 / Contact

Let's talk.

I'm currently exploring new opportunities in full-stack and AI engineering. If you'd like to connect, feel free to reach out.

Built with Angular-era discipline. Deployed with restraint.