GTM Engineer · Account Executive · Revenue Operator
Tam Nguyen
I started as the seller using GTM systems. Now I build them.
I combine frontline sales experience with data, AI, automation, and software: TAM mapping, competitive intelligence, enrichment, account scoring, AI research, outbound infrastructure, and CRM workflows.
About
Why are we asking expensive salespeople to do work software can do better?
My degree is in Management Information Systems, and I started as a business analyst at Constellation Energy and AECOM, building the data and analysis behind their business development teams. Then I moved to the revenue side: SDR, SDR Team Lead, and Account Executive at FiscalNote, then Account Executive at Quorum.
Analyst, seller, builder. I've worked with the data behind the strategy, carried the number, and built the systems in between.
At Quorum, while carrying a quota, I scanned 50,000+ prospect websites in three days to find 5,000+ companies already paying competitors, and cut my account mapping from four hours a day to 30 minutes. Today I build GTM intelligence infrastructure that runs 100 to 500 AI research agents across an entire market overnight.
I've carried the quota, managed the territory, and built the pipeline. Now I build the systems that do the work sellers shouldn't have to.
Full resume and cover letter hereHow I build GTM systems
Six steps from a market to a working pipeline.
The same order every time. Each step has a real project behind it.
Find the whole market
Identify the entire addressable market, including the companies a vendor database never lists.
Shown in RoutePro and GTM Intelligence Engine
Turn businesses into accounts
Multi-source enrichment with fallback paths, reaching about 95% coverage from niche databases, providers, public data, and AI research.
Shown in GTM Intelligence Engine
Find the why now
Observable reasons to reach out today: hiring, reviews, competitor usage, expansion, technology changes, growth.
Shown in Competitive Intelligence Engine
Rank where time goes
Combine ICP fit, signals and potential value into a ranked list, so reps start each day with the best accounts.
Shown in RoutePro
Turn intelligence into conversations
Sending infrastructure, personalization, sequencing, and CRM workflows that hold up at 500,000 emails a month.
Shown in Outbound Infrastructure
Feed results back in
Measure meetings, opportunities, seller capacity and pipeline, and use it to adjust targeting, scoring and messaging.
Shown in Outbound Infrastructure
Code for the math, AI for judgment
Scripts handle scraping, joins, counts and checks. AI handles classification, research and writing. A script then checks the AI's output before anything moves on.
Unknown stays unknown
Missing data is left blank and flagged, never scored as zero. Scores inferred by AI are capped at a lower confidence than sourced data.
Judged by pipeline
I measure a system by the meetings and pipeline it produces. The number of automations shipped doesn't count.
How I think
The common thread is leverage.
It isn't a particular AI model, enrichment provider, or automation platform. When I look at a revenue organization, these are the questions I ask.
- 1Where are sellers spending time that doesn't require a seller?
- 2What information is missing from the CRM?
- 3Can we map the entire market instead of buying another static list?
- 4What signals tell us why an account should be contacted now?
- 5Can we turn successful individual workflows into systems the whole organization can use?
- 6Did what we built improve meetings, opportunities, seller capacity, pipeline, or revenue?The one that matters most.
Selected projects
Things I've built.
GTM Intelligence Engine
Researches an organization's entire addressable market with 100 to 500 parallel AI research agents: about 50,000 companies overnight, about 95% enrichment coverage, 30-day refresh cycles.
Competitive Intelligence Engine
Scanned 50,000+ prospect websites in about three days and found 5,000+ companies already paying competitors, then turned them into displacement campaigns.
Read case studyRoutePro
Turns fragmented local-business data into mapped, enriched, Tier A/B/C territories. One modeled 35-mile territory surfaced 8,378 facilities.
Read case studyOutbound Infrastructure
500+ sending domains and 1,000+ inboxes supporting about 500,000 targeted emails a month, with bounce rates under 3% and 1 to 3% response rates.
Experiments
What I'm testing right now.
Open questions, some with early data. None of these are finished products.
Local TAM mapping
How close can public and commercial data get to listing every business that matches an ICP?
So far: web search adds about 21 to 27% more real companies on top of Google Maps for fire protection and grease trap services.
Hiring signal detection
Can job postings predict when a company is investing in a particular GTM function?
So far: 6,294 postings scraped and scored.
Competitor customer discovery
Can case studies, reviews, integrations and public data reveal a competitor's customer base?
Review intent detection
Can Google reviews identify companies with the exact problem a product solves, such as missed calls at a restaurant?
Stack
Tools I've built with.
Data and enrichment
- Clay
- OpenMart
- Overture
- Prospeo
- Apollo
- Serper
- Apify
- Google Maps
- Sales Navigator
AI
- Claude
- OpenAI
- ChatGPT
- Gemini
- OpenRouter
- Multi-agent research
Automation
- n8n
- APIs
- Webhooks
- Custom scripts
Outbound
- Instantly
- Smartlead
- PlusVibe
CRM and revenue
- Salesforce
- HubSpot
- Attio
- Gong
- Outreach
- Salesloft
Development
- Claude Code
- Next.js
- TypeScript
- Python
- PostgreSQL
- PostGIS
- Mapbox
- Vercel
Experience
Where I've worked.
- FounderCurrentD3 Revenue · revenue engines for B2B companies, from market intelligence to pipeline
- Account Executive / GTM Engineer2024–2026Quorum · hypergrowth B2B SaaS · official title Account Executive
- Founder / GTM Engineer2023–2025Data Driven Revenue · about 12 B2B clients, including RevOps for Adaptive.build
- SDR, SDR Team Lead, Account Executive2021–2023FiscalNote · hypergrowth B2B SaaS
- Business AnalystEarlierAECOM · Fortune 500 · built the data models behind the business development organization
- Business AnalystEarlierConstellation Energy · Fortune 500 · data, analysis and pre-sales support for business development
- Founder, e-commerce operationEarlierAbout $3.6M in revenue
Hiring a GTM Engineer?
I bring the experience of someone who has carried the quota, managed the territory, built the pipeline, found the bottlenecks, and then built the systems that solve them. Happy to walk through any of it live.
- linkedin.com/in/tamnguyen789
- Based in
- Houston, TX