Hello I'm
AI Strategy & Engineering Leadership
I'm Skinner. I've been building things with computers for over 20 years — starting in my grandfather's garage, soldering wires onto microcontroller buses and pushing code down to them. That hands-on instinct stuck. Before coming back to tech, I ran a web development business for a decade, then spent four years in freight operations and procurement — managing 200+ people, $250M in carrier contracts, and national accounts like Walmart and Costco. Those years taught me how big businesses actually work at the operational level.
Today I lead Cloud Engineering and Data Engineering — two teams, five people — at a global public SaaS company, working across the organization. I helped shape the data architecture behind an internal gen-AI assistant adopted at scale, with measured productivity impact per employee. I'm implementing Apache Iceberg as our data lakehouse foundation and shipping ML into the business — cash forecasting for accounts receivable and self-serve modeling for Sales and Marketing via BigQuery ML. I manage $1.3M/yr in cloud spend across three CSPs and a vendor portfolio that includes Snowflake, SAP, Fabric, Tableau, and Alteryx.
What I care about: taking AI from demo to production. Safe, predictable systems that people trust and use every day — not science projects. The best AI work starts with understanding how the business actually runs, then building the thing and measuring what changed.
AI is only useful when it ships and people use it. The gap between a promising prototype and a production service that thousands of people rely on daily is where most AI initiatives fail. That gap is an engineering and change management problem, not a research problem.
I focus on closing that gap. On our internal gen-AI program, that meant designing architecture and operating model together: guardrails that rein in hallucinations and keep behavior predictable, evaluation as usage grew, and sitting with teams across departments to understand real workflows before automating them — not after.
Most enterprise processes were designed around humans doing repetitive work. The tooling has finally caught up. Agentic AI, workflow orchestration, and evaluation frameworks let you automate and augment work that wasn't feasible even two years ago. The teams that move fast and stay disciplined are the ones that pull ahead.
I find the places where AI actually helps — not every problem is an AI problem. I dig into how teams work, figure out what's worth automating, design the architecture, and measure what changed. Our internal assistant started as one workflow pilot, then scaled to company-wide adoption with tracked outcomes.
I run cloud and data engineering teams at a public SaaS company. I hire, coach, and ship alongside my group. I've led change management for AI, analytics, and ML adoption across departments — the hard part isn't building the tool, it's getting people to trust and use it.
I design and build the platform layer: inference services, model hosting, evaluation pipelines, and guardrail systems. The goal is AI that's safe, fast, and cheap enough to run at scale — not just accurate in a notebook.
I stay hands-on. I write code, review architectures, and debug production issues alongside my team. Credibility comes from doing the work, not delegating it.
Every initiative needs a number attached. Our internal gen-AI rollout succeeded because we could tie it to hours saved per employee per year and a steep climb in daily active use — not because the demo was flashy.
Big bang launches fail. I run pilots, collect feedback, iterate, and scale what works. The program started with one team before expanding company-wide.
People won't use tools they don't trust. I design AI systems with guardrails, explainability, and predictable behavior from day one. Change management is part of the build, not an afterthought.
Elastic, Inc.
May 2022 - Present
Lead Cloud Engineering and Data Engineering teams (5 reports, cross-functional). Partner with product, security, and business stakeholders on enterprise AI and data initiatives. Helped design the software, data architecture, and deployment strategy for ElasticGPT — internal AI assistant with 2,100+ users, 125K+ chats, 400K+ interactions, saving 63 hrs/employee/year (92% DAU increase). Introduced Apache Iceberg as the lakehouse foundation for analytics and ML. Shipped ML into operations: AR cash forecasting and self-serve models for Sales and Marketing (BigQuery ML). Implemented Spark, reducing data processing compute cost by ~70%. Migrated NetSuite from 2,200 objects to 60, enabling SOX-compliant real-time financial reporting and AI-ready data. Led change management for AI, data analytics, and ML adoption across departments.
Pluralsight, Inc.
Apr 2021 - May 2022
Designed enterprise cloud architecture for insights, data engineering, data science, and ML teams. Migrated ML pipelines from batch SageMaker jobs to real-time Kafka-based prediction serving. Managed $3.2M/yr cloud spend across AWS, SageMaker, and Snowflake.
LP Building Solutions
Feb 2020 - Apr 2021
Migrated 29 on-prem manufacturing locations to Azure over 19 months at petabyte scale. Cut data processing time by 70%, enabling real-time manufacturing defect detection. The resulting ~2% defect reduction per plant generated $120M in additional annual revenue — the throughput equivalent of a 30th plant without building one. Built integration layer connecting ERP, supply chain, and logistics systems. Nominated for 2019 Nashville Technology Council Technologist of the Year.
LP Building Solutions
Nov 2018 - Feb 2020
First role back in tech after the operations and procurement years. Built data models and reporting for corporate finance, logistics, and supply chain operations across a $4B revenue manufacturer.
LP Building Solutions
2016 - Nov 2018
Managed $250M/year in freight carrier contracts across LP's North American logistics network. Evaluated carriers, negotiated rates, and handled vendor relationships for a $4B manufacturer.
Western Express
2012 - 2016
Managed freight operations across 37 of 48 operating states, accounting for $10M of $15M in weekly billed freight (67% of company revenue). Oversaw 25 managers, each with 40-50 drivers — over 1,000 people total. Served national accounts including Walmart, Target, Costco, Sam's Club, BJ's, and Campbell's. Reduced driver layover 4.6% month-over-month, decreased deadhead 9% year-over-year, and improved delivery throughput 7.5% for high-volume customers.
SkinnerDev.com
Aug 2002 - Dec 2012
Ran a web and mobile development shop for 10 years — 185 customers, $3M annual revenue, team of 10. Shipped Android 2.2 and iOS 3 apps in 2010 with on device receipt-photo-to-ERP expense parsing — delivering on-device OCR-style functionality years before it was enterprise-ready. Full stack: design, code, deploy, support. Built the business from scratch.
Vanderbilt University
2019-2020
Intensive certificate covering data wrangling, visualization, statistical analysis, and machine learning.
Volunteer State Community College
2006-2007
Associate of Applied Science in Business Administration and Management.
White House High School
2000-2003
2004 Graduate - Technical Path.