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Shikha-code36/README.md

नमस्ते (Namaste)🙏🏻, I am Shikha Pandey!

Software Engineer @ American Express | GenAI & LLM Specialist | Full-Stack Developer

I have extensive experience in the information technology and services industries, with a strong track record of contributing to the development of cutting-edge AI products 💻. I specialize in building production-ready GenAI applications, intelligent automation solutions, and scalable enterprise systems that transform how businesses interact with data and serve users.

Apart from my professional journey, I am a learner 📝 and enthusiastic to learn new tech. I believe you only grow when you learn.

Also, I love solving coding problems on LeetCode, HackerEarth, CodeChef, etc. As you can see I have few repos based on my LeetCode solutions and also Data Structure and Algorithm which you can follow. I write blogs as well on Medium.

🚀 What I Do

  • 🤖 Build production-ready GenAI applications using GPT-4, Claude, and custom LLMs
  • 🏗️ Architect scalable microservices and web applications serving 100,000+ concurrent connections
  • 🔍 Develop intelligent document understanding systems with 99%+ accuracy
  • ⚡ Create real-time data processing pipelines using Kafka, RabbitMQ, and event-driven architectures
  • 🎯 Implement RAG applications, semantic search, and vector embeddings
  • 💼 Engineer enterprise-grade solutions with microservices architecture and cloud infrastructure
  • 📊 Build NLP pipelines for automated business intelligence and data transformation
  • 🔐 Design secure authentication systems with OAuth2, JWT, and role-based access control

💡 Core Expertise

Generative AI & Machine Learning

  • Building intelligent automation solutions with GPT-4, Claude API, and LangChain
  • Developing RAG applications and semantic search using vector databases
  • Implementing prompt engineering, fine-tuning, and model optimization
  • Creating document understanding systems processing 10,000+ documents daily
  • Architecting AI-powered interview assessment platforms with real-time evaluation
  • Working with LlamaIndex, Hugging Face Transformers, and custom NLP models

Backend & API Development

  • Designing FastAPI, Flask, and Django microservices with 99.5%+ reliability
  • Building RESTful APIs and GraphQL endpoints for enterprise applications
  • Implementing event-driven architectures with Apache Kafka and RabbitMQ
  • Creating serverless solutions using AWS Lambda and cloud functions
  • Developing asynchronous processing pipelines with 70% performance improvement
  • Working with Sockets, WebSockets for real-time communication

Cloud & DevOps

  • Deploying containerized applications using Docker and AWS ECR
  • Managing infrastructure on AWS (EC2, Lambda, SQS, S3, Bedrock, CloudWatch, SNS)
  • Working with GCP services (Vertex AI, PaLM API, BigQuery)
  • Experience with Azure OpenAI and Linode
  • Implementing CI/CD pipelines with automated testing and zero-downtime releases
  • Optimizing cloud costs while maintaining 99.9% availability

Data Engineering & Databases

  • Architecting hybrid database solutions with MongoDB, PostgreSQL, MySQL, and DynamoDB
  • Building vector-based retrieval systems using FAISS, ChromaDB, Pinecone, pgvector, and Weaviate
  • Implementing Redis caching and Elasticsearch for high-performance search
  • Optimizing SQL queries achieving 30x performance improvements
  • Managing real-time data streaming and Apache Airflow workflows
  • Working with GraphQL for efficient data querying

Full-Stack Development

  • Creating responsive web applications with React.js, HTML, CSS, and Bootstrap
  • Building both web and window-based applications
  • Implementing WebSocket connections for real-time features
  • Developing live dashboards and data visualization interfaces
  • Ensuring accessibility standards (WCAG 2.1 AA) compliance
  • Working with JavaScript/TypeScript for frontend development

Systems Programming & Performance

  • Developing high-performance applications with C++, Go, and Python
  • Implementing CUDA-based solutions for GPU acceleration
  • Building real-time systems with sub-millisecond latency requirements
  • Working with ARMv7 architecture
  • Optimizing algorithms and data structures for performance

🛠️ Technical Arsenal

Generative AI & LLMs

OpenAI Claude LangChain Hugging Face

Expertise: OpenAI GPT-3.5/4, Claude, Anthropic APIs, Prompt Engineering, Chain-of-Thought, Few-shot Learning, Fine-tuning, Model Optimization, LangChain, LlamaIndex, Hugging Face Transformers, RAG Applications, Semantic Search, Vector Embeddings

Vector Databases & Search

FAISS Pinecone Elasticsearch

Tools: FAISS, ChromaDB, Pinecone, pgvector, Weaviate, Elasticsearch with dense retrieval

Programming Languages

Python Go C++ JavaScript TypeScript CUDA

Web Frameworks & Frontend

FastAPI Flask Django React HTML5 CSS3 Bootstrap

Databases & Storage

PostgreSQL MongoDB MySQL Redis DynamoDB GraphQL

Cloud & Infrastructure

AWS GCP Azure Docker Linode

Services: AWS (EC2, Lambda, SQS, Bedrock, S3, CloudWatch, SNS), GCP (Vertex AI, PaLM API, BigQuery), Azure OpenAI, Linode

Real-time & Message Systems

Apache Kafka RabbitMQ Apache Airflow Sockets

Development Tools & IDEs

Git GitHub VS Code PyCharm Jupyter Sublime Text

🎯 Featured Projects

Tech Stack: C++, WebSocket, CUDA, React.js

  • Architected high-performance real-time cryptocurrency arbitrage detection system with C++ engine processing 10,000+ price updates per second across multiple exchanges
  • Developed WebSocket bridge and live trading dashboard using React.js, enabling real-time market data visualization and automated trading decision support
  • Implemented sophisticated arbitrage algorithms with sub-millisecond latency requirements, demonstrating advanced systems programming and financial technology expertise

Tech Stack: Python, TensorFlow, Deep Q-Learning

  • Developed novel deep learning framework implementing Early Exit strategies in CNNs using Deep Q-Learning (DQN) for dynamic computational optimization
  • Enhanced neural network efficiency by 40% reduction in inference time while maintaining 95%+ accuracy on CIFAR-10 image classification through intelligent exit point determination
  • Published comprehensive research findings and implementation details on Medium, contributing to AI optimization knowledge base and demonstrating technical writing expertise

Tech Stack: Python

  • Created a Python library for competitive programmers with comprehensive utilities and helper functions
  • Published on PyPI with complete documentation and usage examples
  • Open-source contribution helping developers solve algorithmic problems more efficiently

🏆 Achievements & Recognition

  • 🌟 SPOT Award - Recognition for exceptional contribution in building and delivering AI requirements in accelerated timeframes
  • ⚔️ LeetCode Knight - Achieved Knight status with 500+ Data Structures and Algorithms problems solved, demonstrating exceptional problem-solving skills
  • 📚 Open Source Contributor - Created competitive programming Python library with comprehensive documentation published on PyPI
  • ✍️ Technical Writer - Published technical articles on Medium covering AI/ML topics and software engineering best practices

📊 GitHub Statistics

Shikha's Github Stats

🔥 GitHub Streaks

👁️ Profile Views

📚 What Drives Me

  • 📝 Continuous Learning - I believe you only grow when you learn. Always exploring new technologies and best practices
  • 💡 Problem Solving - Love tackling coding challenges on LeetCode, HackerRank, CodeChef, and HackerEarth
  • ✍️ Knowledge Sharing - Writing technical articles on Medium to help the developer community
  • 🚀 Building Impact - Creating AI solutions that transform how businesses operate and serve users

🌐 Explore My Work & Connect

LinkedIn Portfolio Medium Email

💬 Let's Collaborate!

  • 💼 Open to discussing AI/ML projects, GenAI applications, and scalable system architecture
  • 🤝 Happy to help with technical challenges and career guidance
  • 🧠 Practicing Algorithms: I enjoy tackling coding challenges on LeetCode and HackerRank to enhance my problem-solving skills
  • 📝 Python Library: I created a python library for competitive programmers - check out the documentation

Show some ❤️ by starring some of the repositories!

⭐️ If you find my work useful, consider starring the repositories!

Pinned Loading

  1. Data-Structures-and-Algorithm-Patterns Data-Structures-and-Algorithm-Patterns Public

    Data Structures and Algorithms Patterns that I followed ,implemented in Python

    Python 115 21

  2. Object-Oriented-Programming-OOPs-Python Object-Oriented-Programming-OOPs-Python Public

    Object-oriented programming (OOP) is a method of structuring a program by bundling related properties and behaviors into individual objects. In this tutorial, you’ll learn about object-oriented pro…

    Python 71 28

  3. early-exit-cnn early-exit-cnn Public

    A deep learning framework that implements Early Exit strategies in Convolutional Neural Networks (CNNs) using Deep Q-Learning (DQN). This project enhances computational efficiency by dynamically de…

    Jupyter Notebook 7

  4. Competitive-Python Competitive-Python Public

    Python Algorithms Package used in competitive programming

    Python 17 4

  5. Jarvis-AI Jarvis-AI Public

    Python-3 program for a virtual assistant to take commands and fullfill it

    Python 10

  6. ChatServer_with_Socket_Python ChatServer_with_Socket_Python Public

    A simple chat server and client project implemented using Python and socket programming

    Python 15 35