Building intelligent systems with React, Python, LangGraph, and scalable cloud architectures.

Languages: Python • JavaScript • Java • C#
Frontend: React.js • Next.js • Angular • HTML5 • CSS3
Backend: Node.js • Express.js • Java Spring Boot • FastAPI
Cloud: Google Cloud Platform (ACE Certified) • AWS (EKS, MSK, EC2, RDS) • Docker • Kubernetes
AI / GenAI: LangChain • LangGraph • Pinecone • RAG • Agents • LLM Tool-Calling • OpenAI API
Databases: PostgreSQL • MongoDB • MySQL • Redis
DevOps: Git • GitHub Actions • GitLab CI/CD • Jenkins • Terraform • Kafka
Testing: JUnit • Jest • Selenium • TestNG • Cucumber

📌 July 2025 - Present • San Jose, CA (Remote)

• Built production multilingual request management system with React + Spring Boot microservices handling 1,000+ monthly state transitions, deployed on AWS EKS with Kafka event streaming
• Designed REST APIs and coordinated cross-service schemas with 200+ tests, improving deployment reliability by 25% and reducing response times by 40%

📌 September 2021 - August 2023 • Bangalore, India

• Architected Spring Boot microservices for fintech platform serving 100,000+ users with OAuth2 security, service discovery, and API Gateway, reducing latency by 40%
• Led team of 4 developers delivering end-to-end payment processing features with Angular frontend and GitLab CI/CD pipelines, increasing transaction success rates by 25%

🏆 Hackathon Winner | Offline AI-Powered Payment System

Built an offline-first payment verification system that works without internet connectivity, winning first place at a university hackathon.

Tech Stack: Python • Flutter • Bluetooth • QR Codes • On-Device LLM • Vision AI

What I Built:

• Offline verification protocol using Bluetooth Low Energy (BLE) and QR code exchange for peer-to-peer transactions
• Python backend implementing cryptographic validation and digital signature verification
• On-device LLM processing for fraud detection without sending data to servers
• Vision AI models for secure document verification and identity validation
• Full integration with Flutter mobile client for seamless user experience

Impact: Enables secure payments in areas with poor connectivity, protecting user privacy through local processing

📹 Watch Demo | Advanced AI Orchestration System

Production-grade multi-agent AI system that generates comprehensive financial research reports through orchestrated retrieval, analysis, and synthesis.

Tech Stack: LangGraph • LangChain • Pinecone • Snowflake • FastAPI • Docker

What I Built:

• LangGraph orchestration - State machine coordinating 3 specialized agents (Retrieval, Web Search, Analysis)
• RAG pipeline - Pinecone vector database with semantic search across 10,000+ financial documents
• Snowflake integration - Real-time data queries for market metrics and historical trends
• Agent architecture - Each agent equipped with specialized tools and decision-making capabilities
• FastAPI backend - RESTful endpoints for triggering workflows and streaming results

Impact: Reduces financial research time from hours to minutes with 90%+ accuracy

Concurrent Systems Engineering | 8 Design Patterns

Built a production-ready rate limiting system from scratch implementing Token Bucket and Fixed Window algorithms with thread-safe concurrent operations.

Tech Stack: Java 17 • Spring Boot 3 • ConcurrentHashMap • Maven

What I Built:

• Token Bucket algorithm - Automatic token refill with configurable capacity (8 tokens) and refill rates (2 tokens/15s)
• Fixed Window algorithm - Hard limits with per-client IP tracking (5 requests/60s window)
• Thread-safe concurrency - ConcurrentHashMap + synchronized blocks preventing race conditions
• 8 Design Patterns - Strategy, Observer, Factory, Singleton, Decorator, Command, State, Builder
• Real-time monitoring - Observer pattern for rate limit violations and event-driven alerts

Technical Highlights:

• O(1) rate limit checks with lock-free reads for maximum throughput
• Per-client IP isolation using fine-grained locking on individual token buckets
• Configurable strategies swappable at runtime based on user tier (Standard vs Premium)

Impact: Production-ready system handling high-concurrency API traffic with microsecond latency

📹 Watch Demo | Full-Stack Application

End-to-end expert consultation booking platform connecting users with industry professionals for 1-on-1 sessions.

Tech Stack: React.js • Node.js • Express.js • MongoDB • JWT Authentication

What I Built:

• Complete React frontend - Component architecture with React Router and Redux state management
• Authentication system - JWT-based auth with role-based access control (Users, Experts, Admin)
• Booking workflow - Multi-step booking process with availability calendar and payment integration
• RESTful API - Express.js backend with MongoDB for user profiles, bookings, and transactions
• Real-time features - WebSocket integration for instant notifications and chat

Impact: Streamlined expert consultation process with 40% reduction in booking friction

GCP • Terraform • Docker • Kubernetes • GitHub Actions

• Automated infrastructure provisioning on Google Cloud Platform using Terraform
• Deployed containerized applications with Kubernetes and Helm charts
• Built CI/CD pipelines with GitHub Actions for automated deployments
• Implemented VPC networking, Cloud SQL, IAM, and security configurations

Spring Boot • OpenAI API • PostgreSQL • React • JWT

• Microservices architecture (Product, Auth, User, AI services)
• Integrated OpenAI API for intelligent product search and recommendations
• Spring Cloud Gateway with Eureka service discovery
• React frontend with AI-powered search features

MERN Stack • RESTful APIs • MongoDB Atlas

• Full-stack web application connecting pet adopters with shelters
• Secure user authentication with JWT and bcrypt
• Real-time pet listings with search and filter capabilities
• RESTful APIs for adoption requests and shelter management

🏅 Google Cloud Associate Cloud Engineer - Certified cloud infrastructure architect

🔭 Currently building: AI-powered code review system with LangGraph
🌱 Learning: Advanced system design patterns and distributed systems
💡 Exploring: LLM fine-tuning and prompt engineering techniques
🎓 Recently completed: MS in Information Systems from Northeastern University (April 2025)

I believe in building systems that are:

• Production-ready - Not just proof-of-concepts, but scalable solutions ready for real users
• Well-architected - Following design patterns and best practices for maintainability
• Performance-focused - Optimized for speed, reliability, and efficiency
• User-centric - Solving real problems with intuitive, accessible interfaces

I'm actively seeking Full-Stack Engineer and Backend Engineer roles where I can leverage my experience in distributed systems, cloud infrastructure, and AI integration.

📧 Email: paraddi.s@northeastern.edu
📱 Phone: +1 (857) 269-0803
🔗 LinkedIn: Satish Mallikarjun Paraddi
💼 Location: Boston, MA (Open to relocation)
🗓️ Availability: Immediate

When I'm not coding, you'll find me:

• 🍳 Cooking - Experimenting with fusion recipes from different cuisines
• 💪 At the gym - Staying fit and clearing my mind
• 🥾 Trekking - Exploring nature trails around New England
• 🤝 Foster care - Volunteering with local community programs