Generative Ai Data Science

Martin McEnroe

Plano, Texas 732-***-**** ************@*****.*** linkedin.com/in/martymcenroe/

Professional Summary

Innovative technology leader with 15+ years of experience in AI/ML solution architecture, cloud computing, and enterprise-scale implementations. Proven track record of architecting and implementing cutting-edge AI solutions, including Generative AI, in cloud environments. Skilled in translating complex business requirements into scalable, secure, and high-performance AI/ML architectures.

Core Competencies

AI/ML Solution Architecture Cloud Architecture (AWS, Azure, GCP) Generative AI MLOps Python Data Engineering Enterprise Architecture Technical Leadership Strategic Planning Stakeholder Management

Professional Experience

ThriveTech.ai - Plano, TX

Chief Technical Officer and Architect (June 2022 - Present)

- Architected and led the development of an AI-powered athletic performance coaching platform using Generative AI, LLM, and RAG technologies

- Designed cloud-based architecture on AWS, integrating ChatGPT API for personalized coaching generation

- Implemented MLOps practices to maintain model performance and prevent drift in production environments

- Created a user profiling system that adapts AI-generated coaching based on individual performance metrics

Texas Department of Transportation - Austin, TX

AI Strategic Consultant (September 2023 - April 2024)

- Authored a comprehensive 76-page AI strategic plan, outlining 32 epics and 213 use cases for AI implementation across the organization

- Conducted extensive stakeholder interviews to align AI strategy with departmental needs and objectives

- Developed a roadmap for AI adoption, considering technical feasibility, regulatory compliance, and organizational impact

Afiniti - Washington, DC

Vice President, Product (March 2021 - June 2022)

- Led the architectural design and implementation of AI-driven customer experience solutions

- Established Key Risk Indicators (KRIs) for AI application security, implementing criticality levels and exception policies

- Designed and implemented Docker-based, Kubernetes-orchestrated AI applications, optimizing for scalability and resource utilization

AT&T - Plano, TX

Director, Data Science & Artificial Intelligence (AI) (September 2017 - October 2020)

- Led a 45-member team with a $9M budget, driving AI and data science initiatives across the enterprise

- Architected and implemented TAVI (Technician Assistant Virtual Interactive), a natural language AI chatbot for customer interventions, generating $4.5M in savings within 15 months

- Designed the architecture for SNAP, a computer vision tool for technicians, leveraging cloud and edge computing

- Spearheaded polycloud strategy, optimizing AI workloads across AWS and Azure environments

- Personally managed MLOps and DevOps processes to ensure AI model performance and reliability in production

- Leveraged TOGAF framework in developing AI/ML solutions and documenting enterprise architecture

Lead Member Technical Staff, Product Enterprise Architect (May 2013 - August 2017)

- Developed enterprise-wide data science platforms, balancing innovation with regulatory compliance

- Introduced Python and R to a 30,000-person engineering organization, fostering a culture of data-driven decision making

- Project Raindrop: Utilized data science clickstream analytics and full-loop process metrics to identify business processes that could be eliminated or transformed as part of Digital First initiative. Leveraged TOGAF principles in Project Rainbow to re-architect low-utilization applications and restructure them into microservices, resulting in millions in annual savings

- Strategized and executed more than 75 studies in 2 years to identify and analyse root causes, proposing 10 projects to automate order-processing to reduce support cost.

- Implemented enterprise architecture best practices, drawing from TOGAF and Open Group methodologies, to create a microservices-based solution for order fulfillment and management across business products

Education & Certifications

- Master of Computer Science, University of Illinois Urbana-Champaign, IL (2017)

- Master of Science, Electrical Engineering, University of Maryland, College Park, MD

- Bachelor of Science, Electrical Engineering, University of Maryland, College Park, MD

- AWS Certifications:

- AWS Machine Learning Specialty

- AWS Solutions Architect Professional

- AWS Data Analytics Specialty

- AWS Data Engineer

- 4 additional AWS certifications

- Azure: DevOps Engineer Expert, 5 additional Azure certifications

- Cybersecurity: CISSP, CCSP

Patents & Achievements

- Holder of 21 granted US patents in AI, cloud computing, and cybersecurity

- Successfully pitched and secured funding for multiple AI initiatives from Senior Vice Presidents at AT&T

- Implemented Generative AI solution that measurably improved user performance through personalized coaching

- Pioneered data-driven approach for assessing 7,000+ systems for cloud migration at AT&T

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