I'm Kartik Choudhary, focused on building reliable software systems and continuously improving my engineering skills.
My interests include:
- 🧩 Backend & API Engineering
- 🗄️ Databases and data-driven applications
- 🔐 Secure authentication and authorization
- 🤖 AI-powered software
- ☁️ Cloud & deployment
- 🧪 Testing, reliability and production engineering
Engineering mindset: understand → design → build → test → observe → improve.
| Area | Focus |
|---|---|
| 🏗️ Backend | REST APIs, business logic, validation, transactions |
| 🔐 Security | JWT, RBAC, tenant isolation, secure configuration |
| 🗄️ Data | SQL, PostgreSQL, schema design, migrations |
| 🤖 AI | Forecasting, analytics, AI-assisted application features |
| 🐳 DevOps | Docker, Nginx, CI/CD, deployment hardening |
| 🧪 Quality | Integration, validation and security testing |
Languages
Java Python SQL JavaScript C
Backend & APIs
Spring Boot REST API JWT RBAC
Databases
PostgreSQL SQL Flyway
Frontend
HTML5 CSS3 JavaScript React
AI / Data
Python NumPy Pandas PyTorch
DevOps & Tools
Git GitHub Docker Nginx Linux AWS
A full-stack, multi-tenant business platform built around real operational workflows.
Engineering highlights
- 🔐 JWT authentication + refresh-token flow
- 👥 Role-based access control
- 🏢 Tenant isolation
- 🗄️ PostgreSQL + Flyway migrations
- 📦 Inventory & warehouse operations
- 🧾 Orders, invoices, expenses and production workflows
- 🇮🇳 GST/tax business logic
- 💳 Credit-limit enforcement
- 🔒 Optimistic locking and data-integrity protections
- 🗑️ Soft-delete where appropriate
- 🤖 Analytics / forecasting integration
- 🐳 Docker + Nginx + TLS
- 📊 Structured logging and observability
- 🧪 Integration/security testing
- 🔍 CI security scanning
The project is intended to demonstrate production engineering practices, not just CRUD screens.
Repository:
https://github.com/kartikchoudharyaktu
Deep-learning research project using a Vision Transformer approach for dermoscopic image classification.
Focus: image preprocessing, augmentation, computer vision and deep learning.
A responsive personal website for presenting projects, skills and professional information.
Statistics above are generated from GitHub activity rather than manually claimed.
The repository includes a GitHub Actions workflow for generating a contribution-snake asset from actual GitHub contribution data.
Once the workflow has run, the generated asset can be embedded here:
- Advanced backend architecture
- Secure production deployments
- Cloud-native engineering
- Testing and observability
- AI integration with real application data
- Clean and maintainable system design
Readable code > clever code
Real data > dummy data
Tests > assumptions
Security > convenience
Observability > guesswork
Simple architecture > unnecessary complexity
