Professional Summary
Experienced software developer with 8+ years of expertise in software development, cloud infrastructure management, and application containerization. Proficient in Java, Python, C, and C++ with extensive experience in modeling and simulation applications for radio frequency (RF) analysis. Strong background in Linux environments - both professionally and personally, and skilled in leading software development teams, managing cloud-based deployments, and optimizing large-scale systems for government and defense organizations.
Education
Master of Science, Computer Science
George Mason University, Fairfax, VA — May 2021
Relevant Coursework: Analysis of Algorithms, Advanced Algorithms, Distributed Systems, Computational Geometry, Theory & Application of Data Mining, Mining Massive Datasets
Bachelor of Science, Computer Science (Minor: Finance)
University of West Florida, Pensacola, FL — May 2016
Experience
Principal Software Engineer
Cutlass Systems Engineering
- Simulation Modeling: Design, develop, and maintain high‑fidelity simulation models representing real‑world maritime systems for complex system‑of‑systems analysis.
- Object Oriented Development: Lead software development in a Linux environment using Java, C++, and Python, prioritizing Object‑Oriented design patterns for scalability.
- Interoperability & Data Exchange: Define and implement protocols for data and event exchange between simulations.
- API & Tooling: Design and debug robust APIs for 3rd‑party software integration and develop prototype tools.
Computer Scientist
U.S. Naval Research Laboratory (NRL), Washington, D.C.
- Contributed to development and enhancement of Interactive Scenario Builder (Builder), a Java-based 3D modeling and simulation tool for RF propagation analysis.
- Managed Dockerized applications and web services on AWS GovCloud, ensuring scalable, secure, and high-performance deployments.
- Developed "Builder in a Browser" (BIB) by containerizing the resource-intensive Builder and deploying it on AWS GovCloud with a no-VNC configuration.
- Automated the release process using bash scripting and integrated it into CI/CD pipeline with Jenkins, reducing release cycles from one week to two days.
- Conducted regular code reviews in Java, Python, and bash; led migration from GitHub Enterprise to Phabricator and subsequently to GitLab.
- Facilitated team meetings, managed infrastructure planning, and mentored new engineers.
Research Intern - Computer Vision
Air Force Research Laboratory (AFRL), Eglin AFB, FL
- Developed a Python-based georegistration database to associate Earth imagery with geospatial coordinates.
- Utilized Linux-based tools and scripting to build scalable data processing workflows.
Skills
Programming
Java, Python, C++, C, Bash scripting
Cloud & DevOps
AWS GovCloud, Docker, Kubernetes, CI/CD, Jenkins, GitLab
Operating Systems
Linux (primary development environment)
Software Development
Backend systems, Web applications, API development
Experience
Principal Software Engineer
Cutlass Systems Engineering
- Simulation Modeling: Design, develop, and maintain high‑fidelity simulation models representing real‑world maritime systems.
- Object Oriented Development: Lead software development in a Linux environment using Java, C++, and Python.
- Interoperability & Data Exchange: Define and implement protocols for data and event exchange between simulations.
- API & Tooling: Design and debug robust APIs for 3rd‑party software integration.
Computer Scientist
U.S. Naval Research Laboratory (NRL), Washington, D.C.
- Lead the development, cloud deployment, and operational support of Interactive Scenario Builder (Builder), a 3D modeling and simulation tool for RF mission planning.
- Managed end-to-end software development from design to deployment and maintenance.
- Spearheaded cloud adoption by leading migration of Builder's workloads to AWS GovCloud.
- Facilitated cross-functional collaboration with researchers, engineers, and external partners.
- Mentored junior engineers and drove innovation in distributed computing and RF propagation modeling.
Research Intern – Computer Vision
Air Force Research Laboratory (AFRL), Eglin AFB, FL
- Developed a georegistration database linking Earth's imagery with precise location data using Python.
- Collaborated with researchers to improve image recognition and mapping algorithms.
AI/ML Projects
- Deployed a local AI-powered server with open-source GPT model, integrated with frontend for real-time interaction.
- Implemented FastAPI for backend and utilized Hugging Face Transformers for LLM integration.
- Containerized the application using Docker for scalability and reproducibility.
- Conducted large-scale data mining projects using Python, Pandas, and PySpark.
- Utilized Google Cloud and AWS for scalable storage and computing.
- Designed and optimized ETL workflows for high-dimensional datasets.
- Developed and deployed AI-driven applications using TensorFlow, PyTorch, and Scikit-learn.
- Built scalable ML pipelines for data preprocessing, model training, and deployment.
- Worked on predictive modeling, NLP, and computer vision projects.
Cloud & Distributed Systems
Cloud & Software Engineer - U.S. Naval Research Laboratory
- Designed and deployed cloud-native applications in AWS GovCloud for mission-critical defense applications.
- Led containerization efforts using Docker and Kubernetes for improved deployment efficiency.
- Developed and maintained cloud-based data processing pipelines using AWS S3 and EC2.
- Migrated legacy applications to the cloud, improving system availability.
- Developed RESTful APIs for seamless communication between cloud applications and users.
Designed and deployed using AWS S3, EC2, and IAM.
Developed a web-based remote training solution, eliminating physical software installations.
Designed platform using AWS, Docker, and Node.js for interactive sensor data analysis.
AI/ML Projects
- LLM-Based AI Server
- Deployed a local AI-powered server, starting with an open-source GPT model, and integrated it with a frontend for real-time interaction.
- Implemented FastAPI for the backend and utilized Hugging Face Transformers for LLM integration.
- Containerized the application using Docker to ensure scalability and reproducibility.
- Data Mining & Big Data Analytics
- Conducted large-scale data mining projects in graduate school, leveraging Python, Pandas, and PySpark to process and analyze massive datasets.
- Utilized Google Cloud and AWS for scalable storage and computing, running distributed data processing pipelines.
- Designed and optimized ETL workflows to extract meaningful insights from high-dimensional datasets.
- Machine Learning & AI Development
- Developed and deployed AI-driven applications using TensorFlow, PyTorch, and Scikit-learn.
- Built scalable ML pipelines for data preprocessing, model training, and deployment.
- Integrated machine learning models into cloud environments using AWS and GCP.
- Worked on predictive modeling, NLP, and computer vision projects for real-world applications.
Cloud & Distributed Systems
- Cloud & Software Engineer - U.S. Naval Research Laboratory
- Designed and deployed cloud-native applications in AWS GovCloud, improving system scalability, performance, and security for mission-critical defense applications.
- Led efforts to containerize applications using Docker and Kubernetes, improving software deployment efficiency and enabling rapid scaling.
- Developed and maintained cloud-based data processing pipelines, leveraging AWS S3 and EC2 for large-scale data management and analysis.
- Migrated legacy applications to the cloud, eliminating reliance on outdated on-prem infrastructure and improving system availability.
- Developed RESTful APIs to facilitate seamless communication between cloud-based applications and end users.
- Led cloud-based visualization efforts, enhancing the usability of electromagnetic spectrum and RF modeling tools.
- Cloud & Software Projects
- AWS-Based Electromagnetic Simulation Service: Designed and deployed a cloud-native simulation tool using AWS S3, EC2, and IAM.
- Builder in a Browser (BIB): Developed a web-based remote training solution, eliminating the need for physical software installations and reducing costs.
- Optimized Data Storage & Retrieval: Enhanced AWS S3 data management, improving speed and accessibility for mission-critical datasets.
- Near Real-Time Sensor Data Visualization: Designed and deployed a platform using AWS, Docker, and Node.js for interactive sensor data analysis.
Education
Master of Science, Computer Science
George Mason University, Fairfax, VA — May 2021
Relevant Coursework: Analysis of Algorithms, Advanced Algorithms, Distributed Systems, Computational Geometry, Theory & Application of Data Mining, Mining Massive Datasets
Bachelor of Science, Computer Science (Minor: Finance)
University of West Florida, Pensacola, FL — May 2016
Projects & Research
Lead developer and cloud infrastructure manager for a mission-critical RF simulation tool using Java, AWS GovCloud, and Docker.
Developed a Python application leveraging scikit-learn to predict stock prices using historical data from Yahoo Finance.
Implemented the HPR algorithm in C++ to optimize 3D point cloud processing for improved visibility determination.
Built a machine learning model to predict customer churn using user interaction data.
Created a comprehensive C program for date arithmetic with Makefile for streamlined compilation.
For more projects, visit my GitHub.
Technical Skills
Programming
Java, Python, C++, C, Bash scripting
Cloud & DevOps
AWS GovCloud, Docker, Kubernetes, CI/CD, Jenkins, GitLab
Operating Systems
Linux (primary development environment)
Software Development
Backend systems, Web applications, API development
Data & Visualization
RF modeling, Simulation tools, Weather data integration
Version Control
Git, GitHub Enterprise, Phabricator, GitLab, Maven, JIRA
Agile & Leadership
Team mentoring, Agile methodologies