I build software.

Built a .NET MCP server that lets an Azure AI agent find data inconsistencies and open IcM tickets for Microsoft Commerce Core on-call teams.

• Engineered a .NET Model Context Protocol (MCP) server enabling an Azure AI agent to automatically detect data inconsistencies in the Business Vetting platform databases used by Microsoft's Commerce Core organization and open incident (IcM) tickets for on-call teams.
• Built a self-updating catalog of data-integrity checks across several systems that the agent extends in plain English with no redeploy.

Mentored students through technical interview prep, focused on data structures and algorithms in Python.

• Mentored 15+ students each week on data structures and algorithms interview prep in Python.
• Coached students on debugging, code optimization, and whiteboard problem-solving techniques.

Built backend microservices for a sports gear web marketplace and worked with the team in an Agile Scrum process.

• Engineered backend microservices with Node.js, Express, and Prisma to power sports gear search filtering in a web marketplace.
• Collaborated with product managers and engineers in an Agile Scrum process, including weekly code reviews.

Mentored 5 student teams through machine learning projects from start to finish.

• Helped students debug Python and clean and preprocess their data.
• Guided teams through techniques like regression and feature selection.
• Coordinated technical tasks to keep projects on track to completion.

Wrote Python scripts to support a data migration from Lawson to Workday.

• Parsed and reformatted CSV invoice data for the new system.
• Reduced manual data entry through automation.
• Supported a cleaner handoff between systems.

Mentored a high school team during the Break Through Tech Miami Winter Guild program.

• Guided students in designing and building a mobile app prototype.
• Focused the project on a study-group matching idea.
• Shipped a working prototype within a 5-day sprint.

Taught Python and computer science fundamentals to 10+ middle school students in a volunteer-led program.

• Delivered hands-on exercises, games, and live coding demos.
• Made coding approachable and engaging for first-time programmers.
• Helped students build confidence in logic and problem-solving.

Built a music popularity prediction model from a Spotify dataset during a first hackathon.

• Worked with peers to analyze the dataset and train a model in Python.
• Used common ML libraries for the prediction pipeline.
• Gained hands-on experience with data cleaning, visualization, and teamwork.