$500M+
Annual processing volume supported by fixed-income systems
Software Engineer
I build financial software that makes complex workflows faster, clearer, and more reliable.
Mid-level full-stack engineer in Orlando designing distributed architectures, data pipelines, and user-facing applications with Angular, .NET Core, Python, and AWS. Recent work supports $500M+ in annual processing and has improved validation speed, pricing turnaround, and reporting performance across fintech workflows.
Based in Orlando, FL
Focus: fintech, platform, and data-heavy product teams
60+
Validation rules added to reduce CECL submission churn
90%+
Reduction in bond pricing turnaround with Python automation
<10s
Peak reporting latency after SQL tuning and indexing work
About
Engineering with business pressure, data complexity, and operator experience in mind.
I work best on products where system design, data integrity, and user experience all matter at the same time. At Raymond James, that has meant building trading and analytics systems, designing pre-submission validation workflows, and delivering internal tools that help users act with more confidence and less friction.
My strongest work sits at the intersection of product clarity and systems rigor: stable APIs, responsive interfaces, durable data pipelines, and workflows shaped around how real users make decisions. The through-line is measurable improvement, whether that means faster approvals, lower latency, or better developer velocity.
01
Reduce cognitive load
Expose the right information at the right time so analysts and traders can move faster with less friction.
02
Design for trust
Validation, observability, and performance matter more when the system underpins financial decisions.
03
Ship measurable outcomes
Every project should improve a metric that users or the business can actually feel.
Experience
Selected work at Raymond James
Full-stack development across fixed-income trading, credit risk, analytics, and internal productivity systems.
2022 - Present
Application Developer II
Raymond James | St. Petersburg, Florida
Building and scaling enterprise applications with Angular, .NET Core, Python, SQL Server, and AWS for fixed-income trading, CECL validation, analytics, and high-throughput loan-processing workflows.
Fixed-income platform
FiMats trading and mortgage analytics
Led development of a fixed-income mortgage analytics trading system using .NET Core, Angular, C#, and SQL Server to support scalable loan processing across millions of records.
- Processes $500M+ annually
- Improved reliability for production trading workflows
- Built trader portal features for customizable offering data and intuitive controls
Credit risk workflow
CECL pre-submission validation service
Architected a validation layer inside the CECL microservice so users could catch data issues before sending submissions to the Moody's API.
- Added 60+ validation rules
- Reduced average approval cycle by 50 minutes
- Lowered re-submission iterations and improved confidence
Automation and analytics
Inventory pricer and reporting performance
Built pricing and analytics tools with Python, Flask, scikit-learn, and SQL tuning to compress slow workflows into faster, more repeatable systems.
- Cut pricing turnaround by 90%+ using weighted regression
- Reduced peak reporting latency to under 10 seconds
- Supported ML workflows with SageMaker and Redshift pipelines
Projects
Public work and product experiments
A mix of production-minded side projects, API integrations, and data-informed applications.
Featured project
Soleful
Early-stage youth athlete injury risk platform built with React, Vite, and FastAPI. Designed, built, and deployed to production with Plantiga API integration, live and mock API modes, and baseline-driven statistical scoring for real-time movement analysis.
React | Vite | FastAPI | Statistical scoring | Netlify | Fly
Automation
Kalshi Deep Trading Bot
Python trading bot for Kalshi prediction markets with structured research, risk controls, and support for demo and live environments.
Python | Kalshi API | AI-assisted research
Product UI
Orlando Food Picker
React and TypeScript decision tool for choosing restaurants with cuisine filters, random selection, favorites, recent-pick history, and Google Places enrichment for ratings, hours, photos, and travel context.
React | TypeScript | MUI | Google Maps | Optional Supabase sync
API integration
Spotify Lyrics
Flask application that combines Spotify playback data with lyric retrieval to show real-time song lyrics for the active track.
Python | Flask | Spotify API | OAuth2
Skills
Technical range, organized for quick scanning
Focused on the technologies and capabilities that show up repeatedly in shipped work.
Languages and frameworks
- C# and .NET Core
- Python
- TypeScript and Angular
- React
Data and backend
- SQL Server
- Oracle
- Redis
- REST APIs, microservices, and data modeling
Cloud and delivery
- AWS S3, SageMaker, and Redshift
- Docker
- CI/CD with Jenkins
- Git and deployment workflows
Engineering strengths
- System design
- Performance optimization
- Data modeling
- Cross-functional product delivery
Credentials
Education grounded in software delivery and financial technology.
Formal training in information technology and financial technology, plus hands-on AWS cloud certification.
Education
University of Central Florida
Education
University of Central Florida
Certification
AWS Certified Cloud Practitioner
Contact
Looking for an engineer who can move between product, platform, and data?
I am open to discussing software engineering opportunities, especially roles involving fintech, internal tools, APIs, and data-intensive products.