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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 unistd library

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