Garret Noble
Senior Software Engineer | AI Integration & Full-Stack Systems Specialist
Professional Summary
Senior Software Engineer with 8+ years developing high-performance backend systems, real-time web applications, and cutting-edge AI integration solutions. Proven expertise in TypeScript/Node.js, distributed systems processing 1K+ messages/second, and statistical computing applications. Recent focus on AI/LLM integration through Model Context Protocol implementations, real-time data visualization systems, and performance-critical applications.
Core Expertise: AI Integration • Full-Stack Development • Distributed Systems • Real-time Applications • Performance Optimization
Technical Expertise
Full-Stack Development
Frontend: TypeScript, JavaScript, Chart.js, Interactive Visualization, Real-time Systems
Backend: Node.js, Fastify, REST APIs, Python (NumPy, SciPy, Pandas)
Databases: SQLite (Performance Optimization), SQL, NoSQL (ArangoDB)
AI & Modern Technologies
AI Integration: Model Context Protocol (MCP), LLM Agents, AI Tool Development, Prompt Engineering
AI Development Tools: GitHub Copilot, Cline, Open WebUI, LLM-Assisted Development
Advanced Systems: D Language, High-Performance Computing, Concurrent Programming
Message Systems: Apache Pulsar, Kafka, Inter-Process Communication
DevOps & Infrastructure
Containerization: Docker/Podman, GitLab CI/CD, Git
Systems: Linux, POSIX, Memory Management, Process Isolation
Cloud: AWS Batch, Distributed Systems, Microservices
Development Practices
Methodologies: Agile/Scrum, Test-Driven Development (TDD), Systems Optimization
Additional Languages: R, MATLAB, C, Java, Ruby, Lisp (ISLisp)
Numerical Computing: GNU Scientific Library, Scipy, Mir-Algorithm
Professional Experience
Baylor College of Medicine
Software Engineer | NIH ClinGen Project (September 2022 - March 2025)
Led development of mission-critical genomic data processing systems supporting national clinical genomics initiatives
Key Achievements:
- Architected high-throughput message queue system (Apache Pulsar + SQLite) achieving 1,000+ msg/sec processing capacity, enabling real-time genomic variant analysis for clinical decision support
- Optimized database performance reducing time complexity from O(n) to O(log(n)) for message access and insertion through advanced indexing strategies
- Introduced SQL relational databases to the organization, leading technical modernization and improving data consistency across all projects
- Developed full-stack genomic analysis platform using Node.js/Fastify/EJS, significantly reducing manual data processing time for research teams
- Mentored development team in containerization best practices, becoming instrumental in organizational adoption of containerization
Technologies: Apache Pulsar, Node.js, Fastify, SQLite, Docker, Podman, EJS, GitLab CI/CD
Uncountable
Software Engineer | Data Pipeline Specialist (November 2021 – August 2022)
Developed automated data processing solutions for laboratory instrumentation and scientific workflows
Key Achievements:
- Engineered robust Python data pipelines (NumPy/SciPy) processing large-scale daily instrumentation data, substantially improving data accuracy through automated validation
- Reverse-engineered 12+ proprietary scientific file formats, enabling seamless data integration across heterogeneous laboratory systems
- Automated critical customer workflows saving 15+ hours/week per client, delivering substantial efficiency gains per customer
- Significantly reduced data processing errors through implementation of comprehensive validation and error handling
Technologies: Python, NumPy, SciPy, Pandas, Data Pipeline Architecture, File Format Engineering
ExxonMobil Chemical
Technologist | Signal Processing & Analytics (July 2017 – July 2021)
Developed advanced analytical solutions for polymer characterization and materials research
Key Achievements:
- Created sophisticated signal processing algorithms in R for polymer characterization using time and frequency domain analysis
- Developed Ruby-based comparative analysis tools for material samples employing statistical methods for unbiased evaluation
- Collaborated with research teams to implement analytical workflows, contributing to internal research initiatives
- Featured on internal research poster for innovative analytical methodology development
Technologies: R, Ruby, Statistical Analysis, Signal Processing, Materials Science, Research Collaboration
Albemarle Corporation
Research Technician | Catalyst Performance Analysis (March 2016 – July 2017)
Built analytical applications for catalyst optimization and hydrocarbon yield prediction
Key Achievements:
- Developed MATLAB application for catalyst performance analysis and interactive visualization
- Created predictive models for hydrocarbon product yield based on catalyst composition analysis
- Implemented data visualization systems for complex chemical process optimization
- Supported research initiatives in catalyst development and performance optimization
Technologies: MATLAB, Data Visualization, Predictive Modeling, Chemical Process Analysis
Key Projects & Technical Leadership
Statistical Process Control Web Application | Lead Developer
Real-time monitoring system with advanced analytics and interactive visualization
- Architected full-stack TypeScript/Node.js application with real-time data processing and statistical analysis
- Implemented SQLite performance optimizations achieving sub-millisecond query times for time-series data
- Developed interactive Chart.js visualization system with zoom, pan, and annotation capabilities
- Created statistical transformation pipeline supporting multiple distribution types and normality testing
Technologies: TypeScript, Node.js, Fastify, SQLite, Chart.js, Statistical Analysis
Repository: github.com/gtnoble/controlchart
AI Integration Platform | Model Context Protocol Implementation
Type-safe D language framework enabling AI model integration with external systems
- Designed and implemented complete MCP protocol stack with compile-time type safety
- Created secure process isolation system for AI tool execution with automatic resource cleanup
- Developed integration servers for Maxima CAS and NgSpice circuit simulation
- Achieved 100% protocol compliance while maintaining performance and safety
Technologies: D Language, JSON-RPC, AI Integration, Process Management, Protocol Design
Repository: github.com/gtnoble/mcp-d
High-Performance Simulation Framework | Cloud Architecture
Scalable computational physics framework for materials science research
- Architected scalable D-language simulation engine supporting 1D-3D material models with substantial performance improvements over existing solutions
- Implemented advanced optimization algorithms (Gradient Descent, L-BFGS) enabling complex material behavior modeling
- Designed cloud-native architecture (AWS Batch) with auto-scaling capabilities, significantly reducing computation costs
- Achieved near-linear scaling across 32 CPU cores through native optimization and efficient memory management
Technologies: D Language, AWS Batch, Advanced Algorithms, High-Performance Computing
Open Source Contributions
Easy-ISLisp Interpreter/Compiler | Core Contributor
Enhanced C runtime and Lisp library development for production interpreter
Core C Runtime Enhancements:
- Implemented dynamically resized token buffers with efficient sliding window memory management
- Developed thread-safe concurrent output capture over separate stdout/stderr streams
- Corrected floating-point arithmetic overflow/underflow behavior for numerical stability
Lisp Library Development:
- Introduced comprehensive matrix math library supporting vector/matrix operations
- Created string processing library with Python-like functionalities
- Integrated POSIX system calls through a unified
unistdlibrary
Testing & Documentation:
- Refactored core testing macros and added exception handler validation
- Revised Lisp-to-C Foreign Function Interface documentation for improved developer experience
Additional Technical Projects
JumboMessage IPC System | Systems Programming
High-performance shared memory message queue in D
- Developed POSIX shared memory and semaphore-based communication system
- Implemented custom circular buffer with flow control for optimal memory usage
- Achieved RAII-based automatic resource cleanup preventing memory leaks
Repository: github.com/gtnoble/jumbomessage
NgSpice MCP Integration | AI Tool Development
MCP server providing AI access to circuit simulation
- Developed comprehensive type-safe D bindings to NgSpice's C API
- Implemented efficient interval-based data selection using binary search algorithms
- Created advanced vector analysis with complex scale support for circuit analysis
Repository: github.com/gtnoble/ngspice-mcp
Education
University of Houston
Bachelor of Science in Chemistry - May 2014
Minor: Energy and Sustainability