Over 9 years turning ambiguous business problems into working systems, reporting, and BI dashboards at global scale. I'm now applying that same discipline to shipping production tools with AI, on the job and on my own. Folsom, CA.
Client facing business operations and technical delivery leader with over 9 years turning
ambiguous business asks into working systems, reporting, and BI dashboards at global scale. I lead from
discovery to delivery. I get to the core of a stakeholder problem, structure it, and drive a solution across
global teams, backed by PMP and Lean Six Sigma program discipline and MBA level financial acumen.
More recently, I've brought that same approach to structuring problems into building production tools
with AI. I shipped an enterprise dashboard at Oracle, built with Codex, that classifies revenue
automatically, and I independently architected Applymatic, an AI job matching platform
built solo, top to bottom, picking up Claude, GitHub, Next.js, and Supabase along the way. I'm now
looking for a role where working hands on with AI is central to the job, not a side project fit in
around it.
I'm comfortable presenting and influencing from analyst to executive. In practice, that means
translating stakeholder requirements into something development teams can actually build, testing and
confirming deliverables before they ship, and managing both analysts and developers day to day. It's
the role I play best. I'm the central point connecting what the business needs, what engineering builds,
and what actually gets delivered.
When Oracle acquired Cerner, hundreds of transitioning sales reps had no compensation solution. They were being paid entirely manually while the business waited on a fix. I led the effort to migrate their contract data into Oracle's contracting system and build the calculations to pay them correctly. I worked across development, reporting, sales, incentive compensation, and administration to get it done.
At a PI planning session, the team had two options that needed the same development effort. One was automating a brand new policy change. The other was fixing a long standing manual review gap that looked less urgent, but was quietly costing the team hundreds of reviews a year. I pushed to prioritize the older gap. The new policy change would only touch a few hundred orders a year either way, automated or not.
For years, the regional comp admin teams had been logging 200 to 300 compensation issues for review, each one taking up to 2 hours to manually calculate and review. While we had templates and calculation guides available for regional comp admin teams, this was still a slow, highly manual ongoing effort. With no engineering background, using Codex as my coding assistant, I built a calculator and revenue classification model using all of Oracle's policy and calculation methods to ingest contract data and calculate results.
The calculator is a deterministic model that runs on two parallel calculation engines, one per line of business. Each engine runs a stateful, sequential walk through a contract's line items so overlapping, concurrent lines don't overwrite each other's ATR values. I validated the logic against hundreds of contracts with known, precalculated results, checking every output line by line, before signing off with compensation, development, and senior leadership.
A full stack AI job application platform for tech workers, built solo around a human in the loop model: "apply smarter, not more." Every morning, AI scans postings and scores them against your background; you review a daily digest and approve before anything is submitted.
An AI assisted enterprise tool built with Codex that ingests contract data and classifies ATR, ARR, renewal, and expansion revenue in seconds. Replaced a manual review process handling 200 to 300 issue trackers a year, each taking 1 to 2 hours to calculate by hand. Validated against hundreds of precalculated test cases before rollout.
→ Try an interactive recreationThis is a recreation built from scratch for this site, using synthetic sample data and simplified logic I wrote for demonstration. It is not the actual Oracle tool or Oracle's real classification rules. Run the walk below to see how each engine classifies a line as new, renewal, or expansion, and splits its value accordingly.
| Line | Series | Term | Contract Value | Annual Value | Status | Classification | Renewal Amount | Expansion Amount |
|---|