Lead a development team of over 5 members for the Kinatico and VoltaRocks projects. Receive product requirements from managers, break them down into actionable items, and ensure timely completion. Provide mentorship to junior developers, facilitate design and refinement sessions, and monitor progress. Follow agile methodologies including sprint planning, retrospectives, and maintaining a prioritized backlog. Build an internal product for HR using FastAPI, Django, ReactJs, and AWS. Develop a distributed task system with Celery, SQS, and DynamoDB. Create a backend with FastAPI and Django ORM, deploying with AWS CDK and CloudFormation. Utilize CQRS patterns and C# to integrate third-party software. Create API endpoints for data handling from third-party webhooks. Set up cron jobs for systematic data retrieval from third-party sources. Develop AI algorithms for energy consumption prediction using AWS Forecast. Develop and deploy API micro-services to enhance functionality and user experience. Collaborate with AWS components like EC2, ECS, S3, and more for scalability. Establish centralized logging with CloudWatch and S3. Design serverless architecture with AWS Timestream and Aurora for the Volta product. Implement hybrid infrastructure using IaC principles in Amazon AWS. Develop custom scraping scripts for data collection from diverse sources. Utilize AWS CodePipeline and ECR with GitHub for a CI/CD pipeline.

Led a team of over 5 developers and supervised the application requirements. Created and executed a comprehensive database architecture using DynamoDB. Developed APIs for the web application utilizing Python (FastAPI) and AWS technology stack. Incorporated AWS OpenSearch to enhance query performance. Optimized monthly costs associated with AWS services. Integrated Textract, SageMaker, and machine learning models to extract valuable data from documents.

Outsourced projects: student management system, covid detection system. Developed mobile applications aimed at assisting both students and instructors. Designed the architecture and pipelines for the machine learning-based enrollment prediction system. Developed the core application logic and established an API server to serve internal services. Implemented and deployed machine learning and deep learning models.

Conducted research on autonomous vehicle theory. Developed algorithms for autonomous driving car functions, including lane detection and keeping, steering wheel prediction, and maintaining a safe distance. Created a demo application using Unity (C#), integrating Flask (Python) and SocketIO to serve the model. Established a connection between the application and a simulation device (Simcraft).