About
Engineer by training, builder by habit.
Hi, I'm Palmer Jones. Thanks for stopping by. I'm a supply-chain engineer turned applied-AI builder. The first chapter of my career was spent making warehouses and labor operations run measurably better; now I build the AI systems that make content and operations run measurably better. The common thread is the one I learned as an industrial engineer: find the real bottleneck, design a system that fixes it, and prove it with numbers.
What I care about is bringing AI to real operational problems the right way, measured, trustworthy, and grounded in how the work actually gets done. Not vibes, not hype. Systems people can rely on, and that hold up when you check them.
What I do now
I'm a Solutions Architect at AirOps, a platform for AI search and answer-engine optimization (AEO). As people move from Googling things to asking ChatGPT, Perplexity, and Gemini, brands have to earn their way into the answers, and I build the content systems and agent workflows that make that happen: content pipelines, brand rules an AI can actually follow, AEO analysis, and the human-in-the-loop guardrails that keep automated output accurate and on-brand.
It's the same engineering discipline I brought to supply chain, pointed at a new domain: encode the rules, build the guardrails, measure the outcome, and turn one-off fixes into reusable systems. I'm especially interested in where these two worlds meet, bringing rigorous, trustworthy AI back to operations and supply chain, where a small efficiency gain moves a very large number.
The longer story
The path here, expandable for detail:
Solutions Architect · AirOps
I own a portfolio of enterprise customers end-to-end, from onboarding through delivery and renewal, for an AI content-operations platform. Day to day I design AEO analytics setups, build multi-stage content pipelines, encode each brand's voice into rule systems an AI can follow, and design the human-in-the-loop guardrails that keep automated content trustworthy. I also build internal tooling so the work is repeatable across the team, and I treat every quality failure as a system-design problem rather than a one-off correction.
Solutions Architect · LogistiVIEW
I moved from consulting into platform development, joining a small, fast team building a Warehouse Execution System (WES), the software that orchestrates people, robots, and tasks on a warehouse floor in real time. I led the technical side of pre-sales: discovery, tailored proofs-of-concept, demo environments, and answering the hard architecture questions during complex sales. I also finished my graduate certificate in Applied AI during this stretch and put it to work on a real project: intelligent task orchestration and predictive insights for a Fortune 500 customer. It's where my supply-chain background and my AI interest first really merged.
Application Systems Administrator · enVista
I took my programming past spreadsheets and onto the technical side of an in-house Labor Management System (LMS), supporting a Fortune 50 beverage distributor running our software across 300+ North American locations. The highlight: when our travel-mapping logic couldn't handle a client's very large facility, I rebuilt the algorithm so it ran more than a thousand times faster, using modern pathfinding while staying compatible with the legacy UI, and bundling it into a single offline HTML file so associates could use it anywhere, even with no connection. I also owned onboarding and training for the team.
Sr. Labor Management Consultant · enVista
Where my supply-chain career started: implementing labor management solutions (both in-house and third-party) for clients across a range of industries. Labor is one of the largest costs in most facilities, so a small efficiency gain from an engineer can have an outsized impact on the bottom line, and the work rewards creativity and constant iteration. Most of all it taught me to communicate across every level of an organization, from floor associates to VPs, and that the best ideas usually come from the floor.
Education
Operations research, optimization, statistics, and process engineering, the toolkit for making complex systems measurably better. Industrial engineering is, at its core, the discipline of removing waste from how work gets done.
Machine learning, intelligent systems, and how to apply them to real business problems. I took it specifically to bring modern AI into the supply-chain software I was already building.
What I work with
Applied AI & Agents
Supply Chain & Operations
Building & Systems
Data & Visualization
A few things I've made
All projects →
Outside work
Living in the Research Triangle gives me easy access to my favorite things: trips out to the mountains and the beach, the occasional triathlon when I'm feeling ambitious, and a lot of college sports. One ongoing goal is to catch a home football and basketball game at UNC, NC State, and Duke. (If I don't know the answer to something, I'll happily go find out who does.)
Want to talk? Here's how to reach me →