Senior Solutions Consultant · AI Builder

Enterprise SE.
AI-Native
Builder.

11+ years in enterprise pre-sales, building AI-native products that close the gap between technical complexity and real-world adoption. Based in Kansas City.

Pre-SalesSolutions EngineeringLangGraphNext.js 14Claude APISupabaseMCP
LinkedIn ↗GitHub ↗Download Resume ↓
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Loopback Field IntelligenceDemoVault Evaluation PlatformMedici Property SearchBridgr SCIM MiddlewarePresail POC SimulatorG-Sailor Estate MarketplaceLoopback Field IntelligenceDemoVault Evaluation PlatformMedici Property SearchBridgr SCIM MiddlewarePresail POC SimulatorG-Sailor Estate Marketplace
// 01

Selected Work

4 projects
001Live · Phase II
Loopback
Field Intelligence Platform
~13h0 → production · solo full-stack · live app

The tool enterprise SaaS teams don't have — SE field signal structured by AI, scoped by Product, shipped to Linear.

SE submittals get structured into product intelligence in real time. Product teams scope for feasibility, prioritize and push to Linear. Customizable feasibility scoring & metrics with corresponding reporting insights.

Next.js 14SupabaseClaude APIVercelLinear APIResend
closingtheloop.app
Loopback
Field Intelligence
AI Integrations
›Signal structuring — typed JSON output
›Feasibility scoring with org-calibrated logic
›Scoping engine — calibrated to your team's definitions
Architecture
›Real-time bidirectional SE → Product → Linear loop
›5 gap classifications with ACV-weighted pattern detection
›2 role-aware data flows — SE and Product personas
What Makes It Hit
›Solo full-stack — no team, no template
›Production deployed — not a demo, a live app
›6 filterable report dimensions with real-time aggregation
~13hBuild Time
1Sprint · Solo
2User Personas
6Report Dims
002In Development
Demo Vault
AI-Powered Demo Intelligence Platform

Enterprise sales teams invest heavily in demos but have no systematic way to know what's actually working. Demo Vault changes that — AI analysis of recordings scored across performance dimensions, with timestamped coaching callouts and team-level pattern detection.

Next.js 14SupabaseClaude APIVercel
Target Problems
✗No visibility into which demo patterns drive close rates
✗Coaching is reactive and anecdotal — can't review every demo
✗Quality inconsistent across reps, regions, and product lines
Outcomes Achieving
✓Managers coach with data instead of gut feel
✓Reps self-correct faster with structured AI feedback
✓Demo quality becomes a measurable, improvable variable
80%Review Time Saved
AIScoring Engine
003Deployed
Medici
Property Intelligence Portal

Built end-to-end for a Medici Land Governance final-round interview. Live Cook, DuPage & Kane county API integration with Mapbox GL JS, Chain of Title Timeline, Gap & Cloud Detection, Bulk PIN Upload, and a full tokenization flow with ERC-721 certificate generation.

Next.js 14SupabaseMapbox GL JSClaude APIERC-721
3County APIs
6Core Modules
~72hBuild Time
↗
004In Development
Bridgr
Universal SaaS Provisioning Middleware

Enterprise IT teams lose hours every week manually provisioning users across SaaS tools. Bridgr fixes that through a unified orchestration layer connecting identity providers and HRIS systems, with AI-powered connector generation for apps outside the catalog.

Next.js 14SupabaseClerkInngestClaude APIRailway
AIConnector Gen
∞App Catalog
0Custom Dev/App
AutoSelf-Healing
BUILDER
// About

Senior SE at Brightly (Siemens). 11 years closing enterprise deals. Building AI-native products on nights and weekends. Pivoting toward Forward Deployed Engineering and applied AI roles.