I build software for the web and mobile.

Built an AI-powered anomaly detection system in C#/.NET on Azure, replacing a hardcoded detection pipeline with autonomous SQL generation.

• Architected and built an AI-powered anomaly detection system in C#/.NET on Azure Functions, using Azure OpenAI to generate SQL on the fly in place of a hardcoded detection pipeline.
• Implemented the full Reason-Act-Observe agent loop along with security guardrails such as SQL validation, token and timeout budgets, allowlists, and circuit breakers.
• Added end-to-end observability through Application Insights.

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.