class AIEngineer:
def __init__(self):
self.name = "Buvananand Vendotha"
self.location = "Hyderabad, India"
self.role = "AI Engineer & Backend Architect"
def expertise(self):
return {
"AI/ML": ["Computer Vision", "NLP", "Deep Learning", "RAG Systems"],
"Backend": ["FastAPI", "Flask", "Django", "Microservices"],
"Architecture": ["REST APIs", "RBAC", "Event-Driven", "Async I/O"],
"Databases": ["PostgreSQL", "MongoDB", "Vector DBs", "Redis"],
"Frontend": ["React", "Next.js", "Three.js 3D", "TypeScript"],
"Deployment": ["Docker", "CI/CD", "Cloud", "Production Systems"]
}
def currently_working_on(self):
return "Building production-grade AI systems and scalable backend architectures"| AI & Machine Learning | Backend Engineering | System Design |
|---|---|---|
| Deep Learning Models | RESTful API Architecture | Microservices Design |
| Computer Vision (YOLO, CNN) | Authentication & Authorization | Vector Database Integration |
| NLP & RAG Systems | Asynchronous Processing | Database Optimization |
| LangChain Agents | Docker & Containerization | Scalability Patterns |
| 3D Visualization (Three.js) | API Security | Production Deployment |
Advanced AI system with cutting-edge capabilities
Technology: Python
Focus: AI/ML Production System
Architecture: Scalable & Modular
Status: Recently Updated (2 weeks ago)Key Features: Production-grade AI implementation • Advanced algorithms • Optimized performance • Modern architecture
Multi-modal AI diagnostic system with computer vision
Vision: YOLO Object Detection + CNN
AI: Gemini API Integration
Frontend: Streamlit Dashboard
Analysis: Medical Image ClassificationKey Features: Disease detection from medical images • Conversational AI interface • Real-time analysis • Multi-modal diagnosis
Intelligent blog generation using LangChain agents
Framework: LangChain Agent System
AI Model: Google Gemini
Tools: Wikipedia, Web Search APIs
Capability: Autonomous Content CreationKey Features: AI agent workflow • Tool-based research • Automated content generation • Context-aware writing
Advanced deepfake detection using neural networks
Model: MesoNet Architecture
AI: Gemini API for Explanations
Media: Image & Video Processing
Framework: Flask BackendKey Features: Deep learning detection • Human-style explanations • Multi-format support • Real-time analysis
🍽️ Mealzo
AI-powered food delivery platform with personalization
Framework: Django Full-Stack
AI: Personalized Meal Recommendations
Features: Real-time Order Tracking
Payment: Secure Payment IntegrationKey Features: AI-driven recommendations • Multi-role dashboards (Customer/Restaurant/Delivery) • Real-time tracking • Secure payments
Production-ready REST API with enterprise-grade security
Architecture: Containerized Microservice
Authentication: JWT + RBAC
Database: PostgreSQL with Async I/O
Deployment: Docker, Production-ReadyKey Features: Role-based access control • Token refresh mechanism • Async operations • API versioning
| 🏗️ Architecture | 🔒 Security | ⚡ Performance | 🤖 AI Systems |
|---|---|---|---|
| RESTful API Design | JWT Authentication | Async/Await Patterns | RAG Pipelines |
| Microservices | RBAC Implementation | Database Indexing | Vector Embeddings |
| Event-Driven | HMAC Signing | Caching Strategies | LangChain Agents |
| Containerization | Secure API Design | Load Optimization | 3D Visualization |
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🔭 Building production-ready AI systems with scalable backend architectures
🌱 Exploring MLOps, Kubernetes, and advanced system design patterns
🤝 Open to collaborating on innovative AI/ML and backend engineering projects
📫 Reach me at: vendotha@gmail.com
Open for: Full-time opportunities • Freelance projects • Technical collaborations • Open source contributions
⭐ From vendotha with passion for building intelligent systems