Currently focused on AI Engineering and emerging technology. I'm driven by purpose, creativity, and a desire to push myself into experiences that expand how I see the world.
I'm at my best when I'm learning fast, keeping my imagination sharp, building something impactful, and moving toward the edge of what feels comfortable.
I'm a Senior Sales Engineer at CloudZero, where I run technical evaluations and help customers build cost models across cloud, Kubernetes, and AI spend. I've spent six years in technical pre-sales at VMware, Broadcom, and CloudZero — earning trust with engineering teams, articulating complex value to executives, and winning competitive deals.
That work pulled me into building with AI myself. I've shipped tools on the side that enable internal teams: an assistant that answers product questions live on customer calls, a system that surfaces scattered market news into a weekly digest, and a tool that helps AI coding agents write correct cost-allocation code. I like that it's the same instinct as my sales work — just pointed at building the product instead of selling it.
Technical pre-sales at a cloud cost intelligence platform managing $14B+ in customer cloud spend. Run POCs, deliver technical demos, and help engineering and finance teams build cost allocation models across AWS, GCP, and Azure.
Cloud management, security, and application observability post-VMware acquisition. Maintained technical relationships and pipeline during a complex org transition.
Led technical evaluations for VMware's cloud cost management and security platforms. Built the Technical Enablement Program, closed the largest CloudHealth commercial deal, and maintained 90%+ customer renewal rates.
Owned post-sale success for 100+ customers. Built onboarding programs and automated outreach workflows that drove consistent retention above 90%.
Grew pipeline through prospecting and discovery. Entry point into cloud cost management and the SE track.
A few things I've designed and shipped. I care as much about the context design, evaluation, and reliability behind these as the prompts themselves.
An AI knowledge corpus that turns any coding agent into an expert at writing CloudZero CostFormation YAML, the allocation logic that decides how cloud spend gets attributed. Built to work across Claude Code, Cursor, Copilot, and Codex.
- Designed a context architecture that makes agents read a strict ruleset and route through a 9-file corpus before generating, cutting the wrong-but-plausible syntax general models produce by default.
- Built auto-populating org context from a customer's live config plus the CloudZero MCP, with a compact index so context persists efficiently across sessions.
- Packaged one corpus to deploy identically across five AI coding tools by mapping each to its native instruction format.
An automated knowledge pipeline that keeps a Claude Team Project accurate enough to use on live customer calls, spanning 9 code repos, Confluence, and a 104K-line Swift codebase that ships weekly.
- Designed a tiered authority system and uncertainty protocol so the assistant never presents an unverified feature as customer-ready, engineering directly against the confidently-wrong failure mode.
- Built an unattended sync pipeline with launchd, a Google Drive bridge, and Python that keeps knowledge fresh on a schedule instead of relying on manual curation.
- Used Claude to distill a 104K-line Swift and Go codebase into a focused technical reference, working around context limits with graceful degradation.
- Tuned a customer-answer-first response format for real-time use mid-call.
A weekly GTM enablement pipeline that synthesizes AI and competitive market signal into a digest reps can act on.
- Built multi-source ingestion across six external feeds, customer call transcripts, and internal Slack, with a defined spec for signal versus noise.
- Version-controlled prompts and saved fixtures for regression testing, so output quality doesn't drift as the pipeline grows.
- Ran the full pipeline through the Claude CLI with no API key required.
A Next.js app that uses Claude to cull and score large photo sets with intent-aware scoring, built from my own photography work.
- Built a production-style web app in Next.js and TypeScript with Claude doing vision-based image scoring against user intent.
- Created an eval-fixtures harness and Playwright tests to measure scoring quality and catch regressions.
- Designed scoring logic that ranks images by what the photographer is selecting for, not generic aesthetics.