Raphael Prates

Deployed AI generative platform to multiple client environments and implemented pytest-based unit and integration tests achieving 80% coverage; designed a message-level feedback mechanism to capture structured LLM evaluation data for analytics and model improvement.

Directed technical delivery for Motorola Messaging cross-functional teams, built a Jira bot that automated ~60% of bug analysis and drove process improvements using sprint metrics to increase predictability and quality.

Maintained and evolved Motorola and Google Messages apps across multiple Android versions, upgraded legacy components for compatibility, reported critical bugs to Google and authored technical documentation to streamline onboarding.

Developed R Shiny app consolidating 30+ datasets to cut bug investigation cycle time by ~20% and led integration and automation for LATAM smartphone deployments, improving CI/CD reliability and reducing release errors.

Standardized Bash build scripts and engineered automated release and validation pipelines using Bash, Python and R, improving build speed ~15% and increasing production stability.

Delivered smartphone software builds for LATAM markets and built Python automation tools and validation scripts, reducing repetitive configuration work and supporting multi-country version control workflows.

Managed maintenance requests and monitored power generator maintenance as part of electrical engineering internship supporting campus operations.

Completed an MBA program focused on Artificial Intelligence and Machine Learning from 2018 to 2019.

Earned a Bachelor's degree in Electrical Engineering between 2011 and 2017.

Internship in Electrical Engineering involving maintenance request management and monitoring of power generator maintenance.