VAST Data
AI Platforms & Solutions
J focuses on driving quantifiable business outcomes for our customers, concentrating on VAST Data’s unique AI technologies. J brings over 20 years of experience to his current role and, as a former customer, architected and implemented solutions for one of the world’s largest hotel chains.
Prior to assuming his current position, J was a Global Field CTO and System Engineer Manager leading the Central US Hyper Converged business for an OEM. J has built and led successful teams across the country, supporting multiple customer verticals. A passionate leader and recruiter, J enjoys spending time in the field with our customers and partners, building lasting relationships and creating an exciting work environment.
Jul 2024 – Present
Nov 2023 – Jul 2024
Mar 2022 – Nov 2023
2020 – 2022
2019
2018
2016 – 2018
2012 – 2016
2011 – 2012
2010 – 2011
2005 – 2010
Beyond the résumé
A mix of what I’ve built: AI data pipelines, retrieval systems, and heavy automation, from a self-contained LLM lab to the systems behind my own company. Real depth, not vibe coding.
Built a single Docker image that turns raw Common Crawl web data into a tokenized training set with Spark, pretrains a GPT with NVIDIA Megatron-LM, and serves a local LLM (Ollama), RAG over documents, and multimodal vision (CLIP, BLIP captioning, OCR, face analysis), fully offline against an enterprise data platform. A complete AI stack that runs with no internet.
A fully offline clone of the VAST Management System UI, built for sales. A web scraper crawls every link in the live console, captures each page, and stitches them back together under the same URLs as the real product, so navigation feels identical. It serves from a simple Python page with no backend, letting sales engineers walk customers through exactly how VMS works anywhere, even air-gapped. Thousands of lines across the capture and post-processing toolchain, spanning hundreds of routes.
Wrote a Playwright orchestrator that runs from all 50 U.S. state capitals via geo-targeting, performs human-like search and navigation, detects and engages a brand's owned properties, and captures per-city proof, concurrent, resilient, and self-documenting.
EcoLuxe is my beauty and wellness company. I designed, built, and shipped its entire AI platform to production in 30 days, solo: multiple cooperating serverless services, shared state, retrieval-augmented generation, multimodal vision, and human-in-the-loop review.
Runs entirely on Cloudflare Workers. Queries are embedded with text-embedding-3-small and matched against multiple Vectorize indexes (1536-dim, cosine) that keep product, advertising, and creator knowledge separate, with KV for shared state. Retrieved context grounds a multi-model step: a large reasoning model makes the decision while a smaller multimodal model screens images and audio, frame by frame. Outputs are structured and on-policy; anything low-confidence escalates to a human.
As a Global AI Strategist I lead hands-on SDK workshops and keynote and executive briefings that democratize AI for enterprise customers and partners, meeting teams where they are and moving them forward.