• 👀 Interests: Python Development | Cloud Architecture | Microservices | Machine Learning | Information Security | Data-centric Solutions | Scalable Infrastructure
• 💻 Technologies I Use:
• 🌱 Currently Learning: Cloud Infrastructure Optimization | AI-driven Predictive Analytics | Langchain for Conversational AI
• 💞️ Looking to Collaborate On: Open-source projects in cloud automation, scalable microservices, and security-driven applications.
• 📫 How to reach me: Telegram | Email

LightAPI I'm excited to be developing a new Python API framework called LightAPI. This framework aims to simplify and enhance the process of building scalable and efficient APIs with Python. LightAPI focuses on providing an intuitive and flexible interface for rapid development, while integrating essential features for performance and security out-of-the-box.

Key Features:

• 🌟 Modular Design: Build your APIs with a flexible and extensible architecture. LightAPI’s modular components allow you to customize and extend functionality to meet your specific needs.
• ⚡ Performance Optimization: Enjoy high performance with built-in optimizations. LightAPI is engineered to handle high loads efficiently, ensuring your APIs run smoothly even under heavy traffic.
• 🔒 Security First: Protect your API and data with default security measures. LightAPI includes essential security features to safeguard against common vulnerabilities and threats.
• 🔗 Easy Integration: Seamlessly integrate with existing Python libraries and frameworks. LightAPI is designed to work well with popular tools and technologies, making it easy to incorporate into your existing stack.
• 🔧 Developer-Friendly: Streamline your development process with intuitive interfaces and clear documentation. LightAPI is crafted to enhance productivity and simplify API development.

Feel free to check out the LightAPI repository for more details and contribute to the project. I'm looking forward to feedback and collaboration!

Over the years, I have contributed to various industries by applying advanced Python development techniques, cloud infrastructure, and data-centric solutions. Below are detailed examples of my work across several domains:

• Financial Technology:

  • Project: AssetX - Predictive Financial Insights
    AssetX is a financial AI company that leverages stock market data to predict trends and provide actionable financial insights. I contributed to developing their AI-driven analytics platform, which processes large-scale stock data using machine learning models to generate predictions and insights for financial markets. The system is built with Python, integrates cloud services for scalability, and uses Kubernetes for seamless orchestration. AssetX’s platform empowers investors with data-backed financial decision-making tools, enhancing accuracy and reducing market risks.

• Information Security:

  • Project: Chatbot Integration for Security Scores
    Developed an AI-driven chatbot leveraging Langchain and FastAPI, deployed in a cloud environment. Integrated Large Language Models (LLMs) for natural language processing, enabling users to query security scores in real-time. Implemented CI/CD pipelines using Jenkins for automated deployment of Dockerized applications on AWS, ensuring secure, scalable, and resilient systems. Utilized Terraform for infrastructure as code, ensuring consistent and repeatable deployments.
    

  • Project: Centralized Cybersecurity Monitoring (SOC 2.0)
    Built a threat intelligence system focused on security operations centers (SOC). Developed REST APIs using Django and Flask to collect, aggregate, and visualize security KPIs and KRIs. Conducted automated vulnerability scanning and pentesting following OWASP methodologies. Integrated the system with RabbitMQ for asynchronous communication and deployed it using Docker and Kubernetes for scalability and fault tolerance. Utilized Terraform for infrastructure management and Jenkins for CI/CD workflows.
    

• Biotechnology:

  • Project: Bioanalytical Platform with AI Integration
    Led the development of a bioanalytics solution, migrating legacy systems from Azure to AWS. Designed Flask-based APIs integrated with SQLAlchemy for high-performance data access, allowing bioanalytical data to be processed efficiently. Implemented machine learning algorithms for predictive modeling, enabling advanced health data analysis. Deployed the system using AWS services and Terraform for infrastructure management.
    

• Banking and Financial Services:

  • Project: Financial Transaction Validation System
    Developed and tested a robust system to add new financial transaction types to a high-volume payment processing platform. Utilized Kubernetes for automated testing in QA environments and built Python-based test suites to ensure the integrity of database transactions. Implemented CI/CD workflows using Jenkins for continuous deployment and validation across multiple development stages, with Docker and Terraform for consistent environments and infrastructure management.
    

  • Project: Automated Stress Testing for Web Applications
    Designed and implemented a large-scale stress testing tool for a cloud-based financial system. Using Python, WebSockets, and HTTP requests, simulated over 30,000 virtual operators and 100,000 virtual clients to test system resilience under high load. The solution provided comprehensive reports on system performance and failure points, improving scalability and stability of financial services infrastructure. Deployed the solution using Docker and AWS, managed with Terraform.
    

• Machine Learning & AI:

  • Project: Real-Time Wildfire Detection System
    Developed a real-time fire detection API using TensorFlow and OpenCV for image processing from live video streams. The API processed image frames, detecting wildfire occurrences and delivering responses in under 30 seconds, significantly improving emergency response times. The system was containerized with Docker for efficient deployment in AWS environments, with Terraform managing the infrastructure.