GreenYellow Projects ~- Easy Vision, a system with the data from sectored consumption behavior, a feasibility study is carried out for energy efficiency actions: Nest, TypeORM, GraphQL, RabbitMQ, TypeScript, Jest, Graylog, Postgres, AzureDevOps, Docker

Engie Brazil Energy Company Projects ~Development methodology scrum/Kanban, microservices, microfrontends, Jira Atlassian, React JS, Node JS (Inversify, TypeORM), TypeScript, OracleDB, Docker, Nginx, Kubernetes, CI/CD: Bitbucket, Bamboo, OpenshiftProjects:- SOMAR with augmented reality Socket.IO, mediasoup Azure Kubernetes Service (AKS), Redis Observability: Lens, Grafana, Kibana, Prometheus- SAU (Monitoring System for Power Plants and Substations) Vileve Company Projects ~Development fullstack in projects related two products Vileve company, that are Vileve Pay and Vileve Assistance. Development stack it is JavaScript (ReactJS, React Native e NodeJS), Agile (Scrum, Kanban), gitFlow, AzureDevOps (Docker, Pipelines, Release), AWS (ECS/EKS, Fargate, EC2, S3 Bucket, Route 53, CloudWatch)Projects:- Mobile Vileve Pay: OnBoarding financial transactions, developed in React Native with libraries Redux, Styled Components, Material-UI and publicated in Apple Store and Play Store.- API Click Sign: Robot that manager documents signature with juridic validation through clicksign, developed like an API in Node.js- API Data Migration SQLServer: Robot that manager CRUD between legacy system and current system, developed in Node.js with features APIRestFull, JWT, SQLServer, applying TDD (Test-driven Development), Swagger - Payment Gateway : Platform that intregrated credit card payments between clients into E-commerce, built in React.JS (Redux, Sagas, StyComp), Node.js, TDD, SQLServer, Docker (Docker-compose), CI/CD AzureDevOps, AWS (ECS, Fargate) with archteture in Sensedia

Projects:- UPTOME: Author of the project documentation the UpToMe social network that have a finaly related improve human resources and personal based on the wheel of life concept. Acting like FullStack developer, with development stack JavaScript (React.js (Redux, Sagas, StyComp), Node.js (APIRestFull, Express, JWT)), Agile (Scrum, Kanban), this project had one implementation peculiarity with two database MongoDB (non-relational) and MySQL (relational), aiming performance improve between datas relationals and non relationals. - EXTRATOR Hospital Aliança Rede D’or (Salvador - BA): data scraping (data extracting) migration electron between legacy database Totvs RM and current database Totvs Protheus, a desktop aplication aplicação developted with tecnologies Electron integrateding React.js e Node.js for data extraction in OracleDB PL/SQL.

responsible for the company's information techlonogy sector, working like fullstack developer in web development projects, also as support to employees, realizing taks computer maintenance, internal server and network.I completed the implementation of the cloud service with Terabytes in data, creation of a digital channel on a video platform, where I produced video lessons on the use of the service.

Working in the construction of web systems projects, involving all areas of software engineering, from documentation to full-stack development, also supporting the internal team of employees, performing maintenance activities for machines, internal server and networks.Driven by the idea of ​​the cloud architecture service in the company, I worked on the research, guiding the management on the appropriate service to the company's context as well as at the beginning of the cloud implementation, for the entity's data storage. The creation of a web application aimed at recording hours in project activities by employees was also started, an application that involved the use of MongoDB, ExpressJS, ReactJS and NodeJS (MERN - end-to-end JavaScript) technologies for the development of the API (JSON), aiming to serve the web and mobile application, called SGH - Hour Management System.I also worked together in the planning and implementation of measures against cyber attacks suffered by the company (during the internship) such as Ransomware, data recovery and backup.

The role of the position was in the area of ​​bioinformatics research, the proposed challenge was to create an algorithm that would surpass the performance of others already consolidated in the academic literature, the goal was successfully achieved to optimize performance by 104.85% in comparison, reducing usage of resources up to 84.22%Immersed in artificial intelligence in the field of evolutionary algorithms, the genetic algorithm combined with the proposed Local Search Simulated Anneling was developed in the Python programming language, involving the scikit-learn machine learning library, the UCI Machine Learning Repository benchmark database and the learning tool of Weka machine. The algorithm also submitted a database with Big Data feature. The work was compared to that of another researcher in the area and obtained optimizing answers with Random Forest learning algorithms, J48, PCA feature transformation method and information gain feature selection and chi².