Domino is a scalable, open-source, no-code web platform for creating, managing, deploying and sharing advanced data and AI workflows.With domino- End users can easily build customized data workflows inside an intuitive visual interface, as simple as putting dominoes pieces together.- Developers can easily create and re-use their code, seamlessly distributing it to a whole community of users.- Business will foster a collaborative data-driven environment, where both dev and non-dev teams will actively contribute to the development of data and AI solutions.

I have been responsible for a wide range of technical projects. As Lead Software Engineer, I lead teams of 2 to 7 people in a results-driven environment, overseeing various impactful projects, some of them:- Led team in developing Internal Knowledge Similarity Search, reducing processing time from days to seconds. Tech used: Qdrant vector database, Cohere API, OpenAI API, FastAPI, and AWS Lambda.- Created core API for financial data platform, implementing scalable solutions with AWS Forecast, Lambda Functions, and Step Functions. Tech used: AWS Lambda, AWS Forecast, Step Functions, RDS MySQL, and AWS S3.- Designed and implemented API for Feature Importance Analysis, savings costs in model training filtering out useless data. Tech used: AWS Batch, Flask, RDS MySQL, and AWS S3.- Led creation of <1 Second Big Data Visualization tool for aerospace manufacturer, enabling sub-second response times. Tech used: AWS Glue, PySpark, AWS EC2, FastAPI, and Dash.- Created IoT Data Visualization Platform for custom and fast data visualization of electric IoT data. Tech used: Dash(POC), React, FastAPI, and Google Big Query.- Designed and implemented Role-Based Access Control (RBAC) system for client's platform using MongoDB. Improved security by allowing data access based on user roles. Tech used: MongoDB, GCP, and FastAPI.- Implemented Serverless E-Commerce ETL workflow for Etsy sellers, achieving throughput of over 1500 records per second. Tech used: AWS Lambda, AWS Step Functions, and Aurora RDS.- Developed comprehensive pipeline for Echocardiogram Atrium and Ventricle Disease Identification. Tech used: Django, Computer Vision Models, Keras, MLFlow, MySql, and Azure.- Collaborated on Neuro Data Standardization project, contributing to convert data in a common standard for neurophysiology data using Python Scripts, Jupyter Notebooks, Ipywidgets, and Dash.