Hi, I'm Sanjay Patidar — a Full Stack Product Engineer with a strong product mindset and 12+ real-world projects delivered across serverless, cloud-native, and SEO-first architectures.

I specialize in building production-grade applications that drive measurable business impact — prioritizing performance, scalability, and user-centric outcomes over just shipping features.

🛠️ Domains I’ve worked in:

• 📊 Government-backed insurance (LIC Neemuch)
• 📚 eLearning platforms (Zedemy LMS)
• 📹 Real-time video communication (ConnectNow)
• 📅 Event coordination (EventEase)
• 🤖 AI-powered mobile apps (AgriBot for farmers)

Each of my projects is backed by a real use case, engineered for production-readiness, performance, and long-term scalability. From serverless deployments to client-side rendering and cloud cost management, every project below is a carefully crafted solution.

Author: Sanjay Patidar — Full Stack Product Engineer
Portfolio: sanjaypatidar.in

This Section organizes my technical content from sanjaypatidar.in. It covers Data Structures & Algorithms (DSA) Pattern Recognition and System Design Patterns for FAANG-level preparation. Content is SSR-optimized for SEO and performance, achieving 80%+ interview success across 500+ mentees.

This Section hosts:

1. DSA Pattern Recognition: 15 patterns for FAANG coding interviews, with JavaScript solutions, ASCII diagrams, and proofs.
2. System Design Patterns: 10 patterns for scalable architectures, with trade-offs and case studies.

Tech Stack:

• Frontend: React SSR (Vercel).
• Backend: AWS Lambda + API Gateway.
• SEO/Perf: Metadata, sitemaps, optimized FCP/LCP.
• Visuals: AWS interactive canvases.

A framework for 15 DSA patterns, unifying 1,200+ FAQs with level-based prep (fresher to senior) over 15-20 days. Includes comparative analyses for overlaps (e.g., Sliding Window vs. Two-Pointers). Metrics: 80% technical round success, 500+ FAANG offers.

10 patterns for FAANG system design interviews, with diagrams, trade-offs, and case studies. Includes 20-30 day prep plans, 500+ FAQs, and 75% success for 300+ candidates. Updated for 2025 trends (e.g., microservices).

Hybrid stack for scalability and performance:

• Frontend: React SSR hydration (Vercel).
• Backend: AWS serverless (Lambda, API Gateway).
• SEO/Perf: Metadata, sitemaps, FCP/LCP tuning.
• Viz: AWS interactive canvases for diagrams.

For AI/Cloud/DSA collaborations:

• Email: [email protected]
• LinkedIn: Sanjay Patidar
• GitHub: sanjaydeploys

Response time: ~24 hours.

Live: licneemuch.space
Case Study: Read Full Case

Developed to modernize local LIC officer operations, this project digitizes policy discovery and lead generation through a fast, serverless, and SEO-optimized web platform.

• Frontend: React, Tailwind CSS, Helmet (SEO), Vite
• Backend: AWS Lambda + API Gateway + MongoDB Atlas
• Infra: CloudFront CDN, S3, ACM, Cloudflare DNS

• 3x increase in inquiry submissions
• Indexed in Google Top 3 for local insurance keywords
• Reduced outreach cost by replacing manual promotions
• 2M+ organic impressions

Live: zedemy.vercel.app
Case Study: Read Full Case

Zedemy is a full-fledged learning management system where users read content, track progress, verify certificates, and use an embedded code editor—all on a serverless infrastructure.

• Markdown-based blog system
• Auto-save enabled in-browser IDE
• Certificate generation + verification engine
• SSR-enabled pages with typed.js headers

• Frontend: React, Redux, CodeMirror, Helmet
• Backend: AWS Lambda + DynamoDB
• Deployment: Vercel + GitHub CI/CD

Live: eventunified.vercel.app
Case Study: Read Full Case

Merged two products—EventEase (smart scheduling) and EventPro (team-based CRUD platform)—into a seamless platform with dashboards, authentication, and real-time collaboration.

• Google Calendar Sync
• Paginated tables with filtering & role access
• Redux slices across shared module structure
• Separate dashboards for admins and users

• Frontend: React, Redux Toolkit, Styled Components, React Router
• Backend: Express, MongoDB, Google Calendar API
• Infra: Render for backend, Vercel for frontend

Live: connectnow.vercel.app
Case Study: Read Full Case

A robust peer-to-peer video and file sharing platform built on WebRTC with custom signaling via Socket.io. Includes ICE retry, real-time chat, and media/file delivery.

• One-click calls with incoming/outgoing flows
• ICE server fallback for 3G/unstable connections
• File sharing and base64 message streaming
• Authentication with protected sockets

• Frontend: React, Redux, WebRTC, Socket.io Client
• Backend: Node.js + Socket.io Server, MongoDB

Live: Explore
Case Study: Read Full Case

+-------------------+       +-------------------+       +-------------------+
|   Android App     |       |   Python Backend  |       |   External APIs   |
| (Kotlin Frontend) |       | (LangChain on AWS |       |                   |
| - UI/UX           | <---> |   Lambda/Docker)  | <---> | - Gemini LLM      |
| - STT/TTS (Hindi/ |       | - Prompt Handling |       | - CloudWatch      |
|   English)        |       | - JSON APIs       |       |                   |
| - Chaquopy (Py)   |       | - Monitoring      |       |                   |
| - Offline Search  |       |                   |       |                   |
+-------------------+       +-------------------+       +-------------------+

A multilingual AI chatbot Android app for farmers, providing pinned Q&A, voice interactions, and offline persistence. Pivoted from Expo to native Kotlin for better integrations.

• Hindi/English speech-to-text/text-to-speech
• Typing indicators and offline mode
• Secure API keys on server-side
• Docker-built Lambda layers for backend

• Frontend: Kotlin, Android SDK, Chaquopy
• Backend: Python, LangChain, Gemini API
• Infra: AWS Lambda, Docker, API Gateway, CloudWatch

• SSR for SEO-first Apps: All major platforms use Helmet and pre-rendered content to enable fast indexing and discoverability.
• Modular Monorepo Management: EventEase uses a shared directory with slices split between EventEase and EventPro modules.
• Optimized Cloud Usage: AWS Lambda + DynamoDB + Vercel balance cost and scale with no backend server maintenance.
• Real-World Freelancing: LIC Neemuch was developed from scratch for a real client with formal SRS, MOU, and ₹50K valuation.
• Hybrid Mobile Development: AgriBot leverages Kotlin with Python backend for AI features, ensuring offline resilience and multilingual support.

Because discoverability leads to organic growth. Whether it's insurance leads or blog visibility, metadata, SSR, and HTML pre-rendering are crucial.

Yes. I designed, built, deployed, and maintained all platforms solo—including integrations, testing, and documentation.

Each project is deployed and indexed. LIC Neemuch is used by real LIC officers. Zedemy has a live user base. EventEase and ConnectNow are fully functional and hosted. AgriBot is a downloadable Android app with real-world AI utility for farmers.

I prefer low-maintenance deployments. Lambda + Vercel + MongoDB provide the right balance of performance and cost, especially for early-stage platforms.

Yes. Shared Redux slices, serverless functions, authentication flows, SSR logic, and AI integrations (like LangChain in AgriBot) are reused and customized per use case.

This repository isn’t a list of template-based clones. It’s a curated, engineered set of platforms born from a developer’s journey toward mastering real-world software delivery.

Every decision—SSR, STUN, role-based routing, SEO tuning, caching headers, AI backend chaining—was made with long-term scalability and performance in mind.

For in-depth reading, check out each individual case study linked above.

• Website: sanjaypatidar.in
• Resume: Download Resume
• LinkedIn: linkedin.com/in/sanjay-patidar
• Email: [email protected]