Alysson Ribeiro
Software Engineer
Hello, welcome! Here you can find more information about me and my experience, as well as some occasional blog posts.
- 2024.05Senior Software Engineer
[ Go Postgres Azure Kubernetes Temporal Grafana ]
About the company: Sematell is a company providing infrastructure for Customer Support, handling incoming Messages through a ticket system
Here I actively participate in System Architecture, Development of internal and external services, Pair Programming and upbringing new libraries, technologies and solutions
- 2021.01Senior Software Engineer
[ Go Mongo NewRelic ReactJS NextJS ElasticSearch Kubernetes Azure ]
About the company: Rockspoon is a POS for restaurants, providing a all-in-one solution for small restaurants in California.
At Rockspoon, I participated in Search, Marketplace and Analytics teams.
We utilized Go with Mongo for the entire backend. Most of my job was to architect and implement features for web-services.
Intensive use of Mongo features, such as change-stream, pipeline-aggregation and time-series collections. - 2020.01Front-end Developer
[ C# .NET MVVM Websocket WPF Protobuf AWS ]
About the company: Fluxonaut is a software developed for investors and journalists, with the objective of providing real-time digested information.
At Fluxonaut, I was responsible for developing the windows and the data processing logic on the frontend.
There I learned C# and WPF framework for displaying real-time information for investors.
I refactored legacy code and enhance memory footprint by 30%.
I also implemented from scratch a pipeline for building and digitally signing the executable. - 2019.01Full Stack Developer
[ Go Python ReactJS TypeScript Postgres Prometheus Grafana Kubernetes GCP ]
About the company: Raccoon is a digital marketing company founded by ex-googlers, providing SEO optimization, business inteligence and engineering projects for customers.
At Raccoon I first learned Go, Containerization and Kubernetes.
There I joined from day-1 a video rendering project for segmentation in ads. Using youtube api and google-ads to render different ads for different audiences. We implemented a simple front-end, api and worker connected through a publisher-subscriber to render thousands of videos in parallel on Google Cloud.
We also implemented a very robust observability with Prometheus and Grafana.