Backend (FastAPI)

I developed and optimized a FastAPI-based backend with a focus on security, scalability, and automation. I implemented middleware, OAuth2 authentication, and API key verification to secure endpoints, while configuring API Gateway for rate limits and abuse prevention. API Gateway configurations were updated automatically via a custom script during deployment.

I built over 15 custom endpoints using Pydantic classes for input validation, reducing validation errors by 30%. I implemented custom error messages, automated version control, and set up two logging systems (local and production) for clean logs. Additionally, I created a custom decorator to catch runtime errors and send automatic email alerts.

AWS

I implemented an automated CI/CD pipeline with two AWS CodePipelines (Dev and Pro), integrated with GitHub branches, triggering deployments automatically and cutting deployment time by 40%. The pipeline utilized CodeBuild for environment-specific builds and Amazon ECS with Blue/Green deployment for zero-downtime updates.

I set up an ECS cluster with separate services for Dev and Pro, each with its own Task Definitions, Load Balancers, and Target Groups. I also implemented AWS Route 53 for DNS routing, Secrets Manager for secure API key management, SNS/SES for email notifications, and EC2 instances with appropriate roles and permissions to optimize infrastructure performance.

Azure

I developed a Teams bot using Azure AI Studio with a Retrieval-Augmented Generation (RAG) system. The bot intelligently handled query-based searches and RAG questions, improving response accuracy by 50% and reducing query response times by 40%.

I also experimented with OpenAI API Agents to extend functionality and implemented Adaptive Cards for user interactions in Teams and Outlook, increasing engagement by 30%. All services, including FastAPI and bots, were hosted in Docker containers on AWS ECS, ensuring smooth deployment and scalability.

As a Backend Intern, I developed a Python-based automated system to connect and integrate data from three different websites, utilizing the requests library for API interactions. I applied Charles Web Debugging Proxy to reverse-engineer external APIs, extracting additional information beyond the standard API responses. This project involved designing and automating an API pipeline workflow, which made sequential API calls, processed results, and generated a consolidated final output. I also built modular code components that enabled independent API interactions for flexible data retrieval and processing. By automating the entire workflow, I significantly improved the efficiency of backend data integration and data processing. This project enhanced my expertise in API development, workflow automation, and backend systems optimization.

As a Back End Developer at WonderWeb Digital Agency, I specialized in building scalable APIs using FastAPI and managing server-side logic with Pydantic. I wrote unit tests with Pytest to ensure API reliability and worked on over 25 projects, delivering efficient backend solutions. My work also involved integrating MongoDB for database management and utilizing Docker for containerization.

For more information, visit WonderWeb Digital Agency.

As a Contractor Bot Developer at Tomb.finance, a crypto project, I developed a sophisticated bot for the Telegram platform. The bot was designed to aggregate data from various websites and smart contracts, analyze it, and present the information in a user-friendly and readable format. This included providing essential data to users, enhancing their interaction with the platform. I utilized Python, NumPy, and Pandas for data analysis, and developed REST APIs to ensure seamless integration. My role also involved working with Oracle SQL Developer for efficient database management.

For more information about the blockchain project , visit Tomb.finance.