Lead Solutions Engineer at Orderful. I work the technical side of our enterprise deals. Discovery, demos, POCs, strategy, all of it. When I'm not in deals, I'm building GTM tooling for the team.
I live between sales and engineering. Lately that's meant GTM automation around account research, Clay enrichment, RFP knowledge search, sales-call context, and AI agent workflows.
I believe the future of GTM is engineered, not managed. Better context, cleaner systems, fewer repetitive tasks.
Building Pipestash on the side as a service-led GTM AI automation agency for revenue teams.
Technical
Workflow Automation (n8n, Zapier, Trigger.dev)
Technical
AI Agent Frameworks (Claude SDK, LangChain)
Technical
iPaaS & Data Orchestration
Technical
CRM & SFDC Workflows
Technical
AI / ML Platforms
Technical
Solutions Architecture
Technical
API/MCP Integrations
Technical
MCP
Technical
Languages
Python
Languages
JavaScript
Languages
GTM
Technical Demos & POCs
GTM
Enterprise Sales Cycles
GTM
Stakeholder Management
GTM
Revenue Operations
GTM
Orderful
2024 — Present
Minneapolis, MN
Lead SE at an API-first EDI platform, owning technical sales for enterprise accounts while designing and deploying GTM automation tools and AI agent workflows.
SPS Commerce
2019 — 2024
Minneapolis, MN
SPS Commerce
2017 — 2019
Minneapolis, MN
University of Arizona, Global Campus
2013 — 2015
University of Minnesota, Duluth
2005 - 2010
Proof of work
Short Looms are being added here to show how the systems are scoped, wired, and evaluated. The goal is to make the work easier to inspect without exposing internal customer data.
A sales workflow system that turns call transcripts, calendar context, pipeline state, and coaching history into deal briefs, prep, follow-up, and handoff artifacts.
Loom will show
A Clay and n8n workflow that enriches inbound leads and target accounts, scores fit, and prepares records for sales routing and rep research.
Loom will show
A signal-processing workflow that pulls from calls and internal conversations, classifies recurring themes, and turns customer feedback into useful GTM and product context.
Loom will show
A RAG-backed workflow for finding trusted answers, drafting responses, and keeping reusable RFP knowledge current as product and security details change.
Loom will show
Full SE lifecycle platform covering research, demo prep, coaching, and automated follow-ups. Built on n8n with CRM and communication platform integrations.
Service-led agency focused on GTM AI systems and automation for revenue teams. Work centers on account research, call and customer-signal processing, CRM-connected context, and AI-assisted sales operations.
Autonomous pipeline that aggregates signals from Zoom transcripts and Slack conversations into structured customer intelligence for product and sales teams.
Internal Chrome extension that enables users to build comprehensive integration design documents based on EDI trading partner scope and perform gap analyses across versions. Leverages APIs to extract and compile data into static design docs for external teams building System of Record integrations.
Full-stack RFP workflow app backed by PostgreSQL with pgvector for embedding-based semantic search over an RFP knowledgebase. Supports uploading RFPs to automate response drafting, continuously learning and self-healing as product, security, and capability data evolves.
Waterfall enrichment workflow in Clay that hydrates raw inbound leads and target accounts with firmographics, technographics, intent signals, and contact data across multiple providers. Outputs ICP-scored, routing-ready records into the CRM so AEs get enriched context before the first touch.
A weekly publication for GTM engineers, produced end-to-end by a multi-agent pipeline I built and run. Specialized agents handle discovery, source ranking, editorial synthesis, and publishing that turns raw industry chatter into a curated issue that ships automatically to a web app every week. Half portfolio piece, half dogfood: a GTM engineer using agents to serve other GTM engineers.
Open-source, agentic operating system for account executives. Pull a Granola/Zoom/Teams/Gong transcript and it creates or updates a deal brief; ask for a briefing and it pulls calendar, pipeline, and coaching history into a morning digest; close a deal and it generates a structured CS handover. Includes a post-demo leave-behind generator and a multi-phase AI coaching layer — metrics extraction from call transcripts, LLM-generated insights, and role-based views (AE, Channel, SDR) for data-driven sales coaching. Provider-agnostic (Confluence/Notion, Slack/Teams) with markdown-first storage so data stays portable. Skills share context, chain together, and learn from feedback.
