Backend & AI Engineer • Scalable Systems • ML & LLM Applications

Engineer focused on building production-grade backend systems and intelligent ML/LLM-powered applications.

• Scalable API architecture
• Secure authentication & RBAC
• Transaction-safe database design
• End-to-end ML pipelines
• AI-driven application engineering

Currently deepening expertise in distributed systems, LLM engineering, and high-performance backend architecture.

📫 raj.0123.aaryan.work@gmail.com

Python • FastAPI • Async SQLAlchemy • PostgreSQL • Alembic
JWT (OAuth2) • Argon2 • REST APIs • Transaction Management
Docker • Clean Architecture

Scikit-learn • XGBoost • Pandas • NumPy
MLflow • SHAP • Model Deployment with FastAPI
RAG Concepts • Vector Search Fundamentals

JavaScript (ES6+) • React.js
API Integration • State Management Basics

Docker • Linux • Git • Redis

Tech Stack: Python, FastAPI, PostgreSQL, Async SQLAlchemy, Alembic, JWT (OAuth2), Argon2, Pydantic, Docker

• Designed scalable backend architecture with modular service layers
• Implemented JWT authentication & role-based access control (Patient/Doctor/Admin)
• Built concurrency-safe appointment booking engine preventing double bookings
• Designed normalized relational schema with optimized indexing
• Integrated Alembic for production-grade database migrations
• Structured for extensibility (caching, background jobs, audit logs)

• Secure JWT authentication
• RBAC authorization model
• Relational schema with foreign keys
• Aggregation queries & pagination
• Clean modular backend architecture

• Modular ML pipeline (Ingestion → Validation → Training → Deployment)
• Model comparison (Logistic Regression, RandomForest, XGBoost)
• MLflow experiment tracking
• SHAP explainability
• FastAPI real-time inference API

Building real systems. Scaling intelligently. 🚀