About

Jon Chen

Full-funnel GTM engineer with a revenue specialization.

Jon Chen is a full-funnel GTM engineer based in the San Francisco Bay Area. He builds the automation a growth motion runs on: answer-engine visibility, enrichment and routing, CPQ, and deal-desk tooling.

He is the founder of Campus Dyno, where he builds two products solo by directing AI coding agents: a multi-tenant CPQ platform and GRAPH/OS, a business-graph platform whose agents produce cited, draft-first actions. Alongside the products he runs GTM engineering engagements for venture-backed companies, most recently building a durable GTM enrichment platform for a healthcare marketplace. Before that he spent five years leading Deal Desk and RevOps at Adobe, Box, Otter.ai, and Conga, and he founded J-Curve Racing, a profitable motorsports equipment business.

Notable work includes a multi-tenant CPQ with document ingestion that turns uploaded order forms into templated quotes, native bi-directional Salesforce and HubSpot sync, and an NLU quote assistant with deterministic pricing; a business-graph platform with bi-temporal facts, Postgres row-level security per tenant, and pgvector entity resolution; a GTM enrichment platform with 229 tests and spend-gated provider dispatch; an internal CPQ shipped in 50 days and adopted by 25 users; and the commercial-ops platform behind J-Curve Racing.

Areas of expertise: GTM engineering, revenue operations, quote-to-cash, CPQ, enrichment infrastructure, answer engine optimization, Salesforce, HubSpot, LLM agents with human-in-the-loop design, and AI-assisted software development.

From Deal Desk to GTM Engineer

The common thread across Jon's operating years was the same frustration: enterprise sales teams slowed down by broken or missing internal tools. Pricing approvals took too long. Quote generation required too many manual steps. Reporting meant stitching spreadsheets from three systems by hand. These were solvable problems, but engineering teams were always focused on customer-facing product.

Jon started solving them himself. First with Salesforce automations and CPQ customizations, then by learning to build. When AI coding agents matured, the pace changed completely: he now ships production platforms solo by directing them, with evals, guardrails, and human-in-the-loop as defaults.

Campus Dyno

In March 2026 Jon founded Campus Dyno, a CPQ and RevOps product company. Its two products:

Campus Dyno CPQ

A production multi-tenant Configure-Price-Quote platform on a TypeScript monorepo, 1,150+ commits and 100K+ lines since March 2026:

GRAPH/OS

A multi-tenant business-graph platform for built-to-order and e-commerce SMBs:

Client Work

Jon's current flagship engagement is a durable GTM enrichment platform for a venture-backed healthcare marketplace. It started as 14 one-off prospecting scripts consolidated into one tested package (screening, ICP scoring, persona tiering, deliverability, cross-list dedup) with 229 tests, pluggable providers (Apollo, ZeroBounce, FullEnrich), and spend-gated dispatch with authoring-time gating, run-time preflight, forecast ceilings, and human-approved paid runs. That package is now a deployed, Postgres-backed web app holding the client's outbound universe of 28,811 accounts and 1,099 contacts, where dedup runs as a pre-spend gate before anything reaches a paid provider.

Earlier, at an AI-native SaaS company, he shipped an internal CPQ adopted by 25 users in 50 days, eight internal tools, a Claude-powered sales-intelligence platform, and end-to-end PLG trial infrastructure.

J-Curve Racing

Jon founded J-Curve Racing in 2023 and built its entire software stack himself: a custom commerce and commercial-ops platform that replaced Shopify, QuickBooks, and a CRM stack, with a Three.js 3D wheel viewer fed by a photogrammetry pipeline, a 71-vehicle fitment knowledge base, and an AEO content engine with 87 published articles and a 100+ prompt answer-engine ranking panel across ChatGPT, Perplexity, Gemini, and Claude. Running the business end to end, from race-team and OEM sales through fulfillment, is why the tooling matches the motion.

Technical Approach

Jon's stack centers on TypeScript end to end: React frontends, Node.js and Express backends, PostgreSQL with Drizzle ORM, and pgvector where retrieval matters. AI integrations run on the Claude API and Groq, always with structured outputs, deterministic code for anything with money in it, prompt-injection defenses, and human approval gates before outbound actions. Observability is a default: Datadog, Sentry, Langfuse, PostHog, and OpenTelemetry across the platforms.

What Jon Is Looking For

Jon is interested in roles where revenue expertise and product execution intersect: GTM Engineer, AI GTM Architect, Revenue Systems, and Deal Desk leadership at AI-native or AI-forward companies. He is strongest where the funnel meets the database: enrichment infrastructure, routing, CPQ, deal-desk tooling, and the answer-engine surfaces that now shape how buyers find products.

If you are looking for someone who can identify a revenue problem on Monday and have a working, tested fix in production by Friday, that is the job description he wrote for himself. You can find him on LinkedIn.

Work