Bridging technical AI/ML capabilities with real-world business results. 20+ years across logistics, B2B technical sales, and entrepreneurial consulting—now applying AI to solve complex problems across diverse domains.
I bridge technical AI/ML capabilities with real-world business applications.
With over 20 years of experience across logistics operations, B2B technical sales, entrepreneurial consulting, and security systems, I bring a unique perspective to AI/ML solutions engineering. My diverse background has developed essential skills: translating technical features into business value, managing client relationships, coordinating cross-functional teams, and rapidly learning new domains.
Currently completing TripleTen's AI/ML Engineering bootcamp, I specialize in understanding client business problems, designing AI/ML solutions that address real-world constraints, and managing implementation projects from discovery to deployment.
My unique combination allows me to speak both technical and business languages fluently—ensuring AI/ML implementations that drive adoption, demonstrate value, and deliver measurable results. View my full resume →
Years of Professional Experience
Solutions Engineer
Problem Solver
AI/ML and data science projects demonstrating technical problem-solving and business value delivery
A B2B sales tool for data/tech consultancies targeting small trucking carriers. Instead of spending weeks building a custom demo before a client commits, you drop in their data and the pipeline autonomously produces three deliverables: a Plotly insights report, a public-facing company profile, and a live Streamlit ops platform — all deployed over HTTPS with no manual steps.
A 7-agent autonomous build loop that grew a SaaS prototype over 146 cycles — each cycle plans a feature, writes the code, runs QA, and self-deploys. The result: a working trucking business management app with auth, Stripe subscriptions, AI receipt scanning, and 27 shipped features — built without a line of manual code.
Analyzed 35+ years of gaming industry sales data to forecast 2017 product success across platforms, regions, and genres. Built statistical models to identify success patterns, then translated complex findings into clear marketing recommendations that non-technical teams can act on immediately.
Technical expertise built through projects and 20+ years of professional experience across multiple industries
Interested in working together? Let's connect.