Brayann Luiz

I’ve been in tech for 17 years, working across backend, frontend, DevOps, and QA. I write clean, scalable code and care about good system design. My main stack includes C#, TypeScript, Python, and React. I’ve also worked with Ruby. I’m fluent in English, comfortable communicating across teams and time zones, whether in writing or in conversation. I’m experienced with both AWS and Azure. I've done infrastructure, CI/CD, containers/clusters, and automation. I’ve been using LLMs and other AI tools to speed up my workflow. Whether it’s generating code, automating routine tasks, or even helping me think through ideas. I’ve also built some AI integrations into systems to handle specific jobs more efficiently. These days, I split my time between coding and leading. I still build stuff every day, but I’m also focused on making good technical decisions, unblocking teams, and getting things done without overcomplicating them. Outside of work, I’m either in the kitchen experimenting with recipes or on a track racing professional endurance go-karts. Both require focus, precision, and a little bit of heat. Just like software… Technical Skills: • Languages: C#, Python, JavaScript/TypeScript, Java • Cloud & DevOps: AWS, Azure, CI/CD, Docker, Terraform • Frameworks & Libraries: React, ASP.NET Core, Blazor • Datastores/Caching: SQL, NoSQL databases (e.g., DynamoDB, MongoDB), Redis • Distributed Systems & Messaging: Experience with messaging services such as Kafka, AWS SQS/SNS, RabbitMQ • AI & Machine Learning: Currently studying LLM-driven recommendation systems, focusing on personalization strategies and generative model integration in product pipelines. Have hands-on experience integrating with OpenAI APIs to automate workflows, enhance user experiences, and embed natural language capabilities into applications. • Other: Technical mentoring, team leadership, system performance design and tuning, application security, and optimized software development workflows Interests: - Passionate about software and hardware integration, particularly in SIM racing setups (e.g., telemetry, motion platforms, and input devices) - Designing an AI-powered software solution for endurance karting races, focused on optimizing driver stints, strategy, and real-time decision-making - Exploring how AI can enhance real-time performance analysis, adaptive feedback systems, and immersive simulation experiences - Continued learning in areas such as edge computing, sensor integration, and machine learning applied to user interaction and motorsport environments