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martymcenroe/README.md

Hi, I'm Marty McEnroe: Principal AI Architect & Enterprise Strategist

I am an Enterprise Architect and AI Strategist with a deep background in engineering, cloud infrastructure, and application security (Professional Engineer, 21 patents, former Director at AT&T) focused on designing and executing secure, scalable, and business-driven AI strategies.

My passion is architecting robust, high-value solutions. My architectural philosophy balances elegance and simplicity with a pragmatic focus on execution; I prioritize accelerating the path from concept to robust, working code.

This GitHub is my professional portfolio, showcasing enterprise-ready projects in Generative AI, MLOps, and Cloud-Native Security.

πŸš€ Engineering Portfolio

πŸ”­ Active Engineering

Aletheia β€” Serverless AI Context Analysis Engine A specialized Chrome Extension backend built on AWS Lambda and LangGraph.

  • Architecture: Event-driven, "Scale-to-Zero" Serverless (Python 3.12).
  • Engineering: "Bare Metal" infrastructure (Bash/AWS CLI) with no abstraction layers.
  • AI Logic: Stateful Agentic workflows with local guardrails and validation.
  • Focus: Bridging static web content with semantic AI understanding.

βœ… Completed Prototypes & Tools

GlucoPulse.ai (AI Health) A comprehensive Reference Implementation for a health data platform.

  • Focus: Demonstrating a complete Model Lifecycle (MLOps) for time-series data.
  • Tech: Integrated Snowflake Cortex, Azure ML, and LangChain for GenAI-driven RAG.

NEC 2017 Analyzer A domain-specific Personal Utility for parsing National Electric Code data.

  • Context: Built to automate code analysis tasks relevant to my Professional Engineer (PE) work.
  • Tech: Python-based parsing and analysis scripts utilizing LLM assistance for data extraction.

πŸ“ Architecture & System Design

Iconoscope Enterprise Architecture Specification for an Azure-native video analysis platform.

  • Status: Architecture & Design Phase.
  • Scope: Defines the strategy for a governed MLOps lifecycle (Azure DevOps, MLflow) and a statistically-backed GenAI pipeline.
  • Goal: Blueprint for scalable video insight synthesis.

πŸ› οΈ Technology Stack

  • Engineering: "Bare Metal" infrastructure (Bash/AWS CLI) with no abstraction layers.
  • AI Logic: Stateful Agentic workflows with local guardrails and validation.
  • Focus: Bridging static web content with semantic AI understanding.

  • Iconoscope (AI Video Analysis): An enterprise-ready, Azure-native AI video analysis platform. This project demonstrates a complete AI strategy, a governed MLOps lifecycle (Azure DevOps, MLflow), and a statistically-backed GenAI (RAG) pipeline for insight synthesis.

  • GlucoPulse.ai (AI Health): An enterprise-grade AI health platform demonstrating a complete model lifecycle for time-series data, integrating Snowflake Cortex, Azure ML, and LangChain for GenAI-driven RAG.

  • NEC 2017 Analyzer (Domain Tool): A domain-specific tool for parsing and analyzing the National Electric Code, reflecting my background as a Professional Engineer (PE).

πŸ› οΈ Technology Stack

πŸ€– AI/ML & Generative AI

PyTorch TensorFlow scikit-learn Hugging Face

Frameworks: PyTorch β€’ TensorFlow β€’ scikit-learn β€’ Hugging Face Transformers
LLMs: GPT-4 β€’ Claude β€’ Gemini β€’ Prompt Engineering
Agent Systems: LangChain β€’ LangGraph β€’ LangSmith β€’ Multi-Agent Orchestration
Computer Vision: OpenCV β€’ YOLO β€’ AWS Rekognition β€’ Azure Computer Vision
NLP: BERT β€’ Intent Classification β€’ NER β€’ Text Classification β€’ Semantic Search

πŸ” RAG & Vector Search

Vector Databases: ChromaDB β€’ FAISS β€’ Pinecone
Architectures: RAG Systems β€’ Embeddings β€’ Semantic Search

☁️ Cloud Platforms

AWS Azure GCP Snowflake

AWS: SageMaker β€’ Bedrock β€’ Lambda β€’ S3 β€’ EC2 β€’ DynamoDB β€’ Rekognition
Azure: Azure ML β€’ Cognitive Services β€’ Computer Vision β€’ Functions β€’ DevOps
GCP: Vertex AI β€’ Gemini API β€’ NotebookLM
Snowflake: Cortex AI β€’ Snowpark β€’ ML Functions β€’ Time-Series Analysis

πŸš€ MLOps & DevOps

Docker GitHub Actions

MLOps: MLflow (Versioning, Tracking) β€’ Model Deployment/Monitoring β€’ Lifecycle Management
DevOps: Docker β€’ Jenkins β€’ GitHub Actions β€’ Azure DevOps β€’ CI/CD Pipelines
Code Quality: SonarQube β€’ Penetration Testing β€’ Vulnerability Management

πŸ’Ύ Data Engineering & Databases

PostgreSQL Redis

Databases: PostgreSQL β€’ DynamoDB β€’ Redis β€’ Snowflake
Tools: Pandas β€’ NumPy β€’ Jupyter β€’ Poetry
Pipelines: ELT/ETL Design β€’ Data Quality β€’ Feature Engineering β€’ Data Governance

πŸ”§ Development & APIs

Python TypeScript C++

Languages: Python β€’ JavaScript β€’ TypeScript β€’ SQL β€’ C++
Frameworks: FastAPI β€’ Flask β€’ RESTful APIs
Low-Code ML: H2O.ai β€’ SageMaker Canvas β€’ Azure ML Studio

πŸ”’ Security & Governance

Certifications: CISSP β€’ CCSP β€’ AWS Security Specialty
Practices: Application Security Architecture β€’ OWASP β€’ Penetration Testing
AI Governance: Responsible AI β€’ Bias Mitigation β€’ Data Privacy & Compliance

πŸ“Š Visualization & BI

Tools: Power BI β€’ Tableau β€’ Streamlit β€’ Gradio β€’ SQL Dashboards

🀝 AI-Assisted Development

GitHub Copilot VSCode

AI Assistants: Claude β€’ ChatGPT β€’ Gemini β€’ GitHub Copilot
IDE: VSCode β€’ Poetry β€’ pipx

πŸ“‹ Leadership & Methodology

Management: Jira β€’ Agile β€’ Sprint Planning
Leadership: Architecture Reviews β€’ Team Leadership β€’ SVP Presentations β€’ Technical Mentorship
Strategy: ROI Modeling β€’ Business Cases β€’ Strategic Roadmaps

πŸ“Š GitHub Stats

martymcenroe's GitHub stats martymcenroe's top languages

πŸ“¬ Connect with Me

I am always open to discussing complex architectural challenges, new project ideas, and strategic opportunities.

Pinned Loading

  1. ai-power-systems-compendium ai-power-systems-compendium Public

    An eclectic compendium of AI/ML resources for the Bulk Power System (BPS) and utility sector.

    10

  2. Aletheia Aletheia Public

    Python 2