Madari Venkatesh

Full Stack Developer

Hyderabad, India

Hire me

Hello, World

Hey, I'm Venkatesh, a full-stack developer with 2+ years of experience building and scaling production SaaS applications with React.js, Next.js, Node.js, and Express.js.
I work across the stack, from RESTful API design secured with JWT, RBAC and PBAC to cloud-native, high-availability AWS architecture: EC2 Auto Scaling, ALB, RDS, S3, CloudFront, ElastiCache and Route 53.
I care about performance and reliability, and I back it up with load testing. I build best when I can ship something that holds up in production.

DEVELOPER SNAPSHOT

•Scaling SaaS systems.

•Deploying on AWS.

•Implementing system designs

•Shipping on time.

Let's Connect

GitHub LinkedIn Mail Resume

Work Journey

Full-Stack Developer · Spack Digi Solutions

May 2024 · Present

Designing and shipping scalable SaaS features across REST API services and React.js/Next.js frontends, on cloud-native, high-availability AWS infrastructure.

Years experience

15+

Projects builded

11.5M

Requests load-tested

Production deployments

Work History

Roles at Spack Digi Solutions, Hyderabad.

Full-Stack Developer

Spack Digi Solutions · Oct 2025 – Present

Built REST APIs and React/Next.js features for a production SaaS. Ran EC2 behind ASG + ALB with Nginx for zero-downtime scaling, cached public API responses at CloudFront (validated with k6 up to 11.5M requests at 99%+ success), added Redis via ElastiCache, and secured APIs with JWT, RBAC and PBAC.

Node.jsExpress.jsTypeScriptMySQLSequelizeAWSNginxk6JWTRBACPBAC

Frontend Developer

Spack Digi Solutions · May 2024 – Sept 2025

Redesigned interfaces across 15+ applications with React.js and Tailwind CSS. Implemented permission-based access control and real-time features with Socket.IO, and integrated frontend with backend APIs.

React.jsNext.jsTypeScriptJavaScriptHTMLCSSTailwind CSS

Delivered 3+ freelance projects with 100% on-time completion, resulting in strong client referrals and repeat business.

Field Notes

View all blogs

How to Build a Custom AI Chatbot with RAG Using Gemini, LangChain, Puppeteer.

AI & RAG

25 min read

How to Build a Custom AI Chatbot with RAG Using Gemini, LangChain, Puppeteer.

A step-by-step guide to building a chatbot that answers questions from your own website content. You will scrape pages with Puppeteer, chunk them with LangChain, embed them with Gemini, store everything in MySQL with Prisma and retrieve answers using cosine similarity. You will also build the Next.js API route and a floating chat widget.

RAGGeminiLangChainPuppeteer+2

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System Design & Geohashing

13 min read

How Uber and Rapido Find Nearby Drivers

How ride apps find nearby drivers in milliseconds: Geohash narrows the search, Redis stores live locations and Haversine filters by radius. Worked example included.

GeohashingRedisHaversineGEOSEARCH+1

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My Toolbox

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JavaScriptTypeScriptHTML5CSS3SQLReact.jsNext.jsTailwind CSSSocket.IOResponsive DesignNode.jsExpress.jsREST APIsJWTRAGPrismaSequelizeMySQLRedisEC2ASGALBRDSS3CloudFrontRoute 53NginxGitGitHubPostmank6

Things I've Built

Custom AI Chatbot with RAG

An AI-powered RAG chatbot powered by Google Gemini, built with Next.js, LangChain, Prisma, and MySQL. Companies can customize their chatbot, index website pages, add custom FAQs, and deliver AI-generated answers based on their own website content and knowledge base.

PuppeteerlangchainGemini AINode.jsExpress.jsPrismaMySQL

Hospital Appointment Management System

A full-stack hospital appointment platform with automated doctor scheduling, patient authentication, and seamless booking workflows. Secured with a scalable JWT architecture and PBAC for role-specific dashboards.

Node.jsExpress.jsMySQLPrismaJWTAWS EC2NginxReact.jsTailwind CSS