Front-end = back-end = Django

Implemented internship platform from the scratch with the help of a team.Design database, document, API design/URL.Implemented authentication and authorization using JWT token, design managers, signals, implemented task queues, multithreading concept, and integrated third-party APIs.Hosted project on AWS.

Design database, document, API design/URLImplemented managers, and signals, implemented task queues, multithreading concept, and integrated third-party APIs.It is specifically for restaurants in which owners can create a bill of customers and manage data of foods, their kitchen, and tables.

I have created two projects of ERP with the same functionality.One can run offline means that is a Progressive web application(PWA).And another one is a normal Django project.I have also applied syncing mechanism for both for the requirement of the same data for both projects.And yes also implemented and designed models, APIs, view sets, signals, managers, and middlewares.

Hospital operators can manage doctors data with their respective specialties.They can store medicines respective to IllnessImplemented and designed models, APIs, view sets, signals, managers, and middleware.

I have made this project for my personal useThere are two sites here one for admin (for myself), and one for an agentMy agent adds their sales into that and I can see the sales list, I am also managing the stocks over thereI can also see my earning

I lead the development of algorithmic trading products overseeing a team of developers and participating in both technical and business discussions. My responsibilities include database design using sharding and master-slave architecture REST API development and ensuring high-quality code. We utilize Docker for containerization Jenkins for CI/CD pipelines AWS RDS for database management and RabbitMQ for data transmission. I implemented Nginx with caching and load balancing along with encryption techniques to protect sensitive data. I collaborate with testers and front-end developers document our APIs and deploy code on AWS. My role involves creating and managing JIRA tickets assigning tasks and performing PR reviews. Additionally I developed automation for algo trading using AWS Lambda and created data visualizations for users. I tackle production bugs participate in client meetings and oversee junior team members tasks. My experience in software development leadership and strong communication skills make me a valuable asset to complex trading projects.

In the project Im actively engaged in I harness the capabilities of Python to automate the integration of two essential security tools Invicti and Veracode into our workflow. This automation facilitates the efficient identification of vulnerabilities within our project and the automatic creation of issue tickets in Jira for streamlined management. Leveraging the power of Docker we containerize our applications ensuring consistency and ease of deployment. We store and manage these containers using AWS Elastic Container Registry (ECR) while our applications run seamlessly on AWS Elastic Compute Cloud (EC2) instances. Additionally we employ AWS Lambda functions to orchestrate various tasks enhancing the scalability and efficiency of our processes. To ensure the robustness and maintainability of our Python code we adhere to best practices and utilize Python design patterns enabling us to write clean efficient and maintainable code. This comprehensive approach enhances security reduces manual effort and fosters seamless collaboration between our development and security teams ensuring the swift resolution of potential threats and the delivery of secure software.

Developed a robust system leveraging both open-source and closed-source models for natural language processing and machine learning. The project integrated models from Hugging Face (open-source) and APIs from OpenAI and Gemini (closed-source) to deliver powerful AI-driven functionalities. The system allows users to upload PDF CSV Excel and MP3 files and obtain answers via API. Users can compare and rate answers from multiple LLMs fostering better insights and decision-making. Handled Docker for containerization AWS for deployment Nginx for load balancing and caching and Jenkins for CI/CD pipelines managing the DevOps aspect to ensure seamless integration and deployment processes. Developed REST APIs and business logic in Python implemented file validation worked with pickle files and vector databases and built a strong error-handling mechanism. Additionally created a chat and conversation system for dynamic user interactions. Led the development of the product coordinating between various teams and ensuring timely delivery of features and enhancements. This comprehensive approach ensured high reliability stability and efficiency of the system providing a versatile and powerful tool for users.

Our project centers around a customized pizza ordering platform with a Flask-based microservice architecture powering the backend. This innovative platform seamlessly integrates with renowned third-party delivery services such as DoorDash Uber Eats and SkipTheDishes. At its core it empowers customers to craft personalized pizzas tailored to their exact preferences putting them in control of every delicious detail. The project utilizes a dual-database approach for efficient data management. Google Cloud Platforms Datastore a NoSQL database handles non-relational data while PostgreSQL manages structured relational data ensuring data integrity and scalability. To automate tasks we rely on Jenkins ensuring that our workflow is streamlined and efficient. Adhering to Python best practices outlined in PEP 8 we maintain clean and readable code. We prioritize code quality through extensive unit testing and integration testing validating the robustness and reliability of our platform. In summary our Customized Pizza Ordering Platform represents a fusion of culinary creativity and technical excellence. It empowers customers to design their dream pizzas while adhering to the highest standards of software development and automation.

I built and developed an ERP system using FastAPI managing the entire lifecycle from development to deployment. This included Dockerizing the application and hosting it in AWS ECR and ECS. I implemented load balancing and a rolling update strategy to ensure zero downtime and I created task definitions and clusters for efficient management. I built multi-stage Docker images to optimize memory usage. Additionally I handled all database design API documentation task distribution and DevOps tasks including setting up message queues with RabbitMQ and configuring Nginx.

Our healthcare-focused project revolves around a Django REST API-driven backend simplifying the intricate task of code auditing within clinical charts. The system involves multiple essential roles including coders L1 and L2 auditors culminating with L3 auditors as the final authority. These auditors diligently review medical codes within clinical charts ensuring accuracy and compliance. To manage data efficiently weve employed Django database routing which enables us to work with multiple databases keeping sensitive healthcare data segregated and secure. For robust security measures weve implemented SAML and OneAuth authentication methods safeguarding sensitive patient information. Our commitment to performance optimization is evident through our use of a master-slave architecture and sharding techniques ensuring that our database operations remain efficient and scalable. Our tech stack includes Celery and RabbitMQ for asynchronous processing Azure-based CI/CD pipelines for seamless deployments and Docker for containerization. Nginx serves as our web server guaranteeing reliable and high-performance application delivery. This project underscores our dedication to simplifying healthcare coding processes while prioritizing data security and performance.