I build the signal systems that turn your data into pipeline.
Through AI GTM Engineering, I design and deploy the enrichment, scoring, and routing infrastructure that tells your sales team exactly who to call, why, and when.
Get a Free Signal Diagnostic →You'll walk away with three prioritized changes for your GTM motion—whether we work together or not.
Your GTM motion has a signal problem.
You have more buying signals available to you right now than at any point in history. Seat growth in your product. Champion job changes. Funding rounds. Hiring surges. Tech stack shifts. Competitor churn.
And your team is acting on almost none of them.
Not because they're lazy. Because the infrastructure to capture those signals, score them, enrich them with context, and route them to the right rep at the right time doesn't exist yet in your stack.
So your reps do what they've always done: work a static list, send generic sequences, and hope the timing is right.
Meanwhile, the companies that have built signal infrastructure are operating in a different reality. Their reps only talk to accounts showing active buying behavior. Their outbound converts at 3–5x the industry average. Their pipeline isn't a forecast—it's a measurement.
The gap between those two realities is exactly what I close.
The Method
The Signal Architecture™
A five-phase system for turning raw data into pipeline you can measure.
Every engagement starts from the same conviction: the best outbound isn't about volume. It's about signal quality. The question isn't "who could we sell to?"—it's "who is showing us, right now, that they're more likely to buy?"
The Signal Architecture uses AI and automation at every layer—from LLM-powered enrichment and intelligent scoring models to AI agents that monitor signals in real time. This isn't about sprinkling AI onto existing workflows. It's about building GTM infrastructure where AI is the engine, not an add-on.
Audit
+I map your existing signal landscape and AI readiness. What data sources do you have? What are you acting on today? Where can AI-powered enrichment and automation close the gaps? You get a signal coverage scorecard, a prioritized gap list, and an AI opportunity map for your GTM motion.
Design
+I architect the scoring model, AI-driven enrichment pipeline, and routing logic specific to your ICP, sales cycle, and team structure. This includes designing which AI agents handle which tasks—from LLM-powered research enrichment to automated signal classification. Deliverable: a documented signal architecture blueprint your team can review before a single workflow is built.
Build
−Clay workflows, AI enrichment agents, CRM integrations, LLM-powered scoring algorithms, intelligent routing rules. This is where the architecture becomes AI-native infrastructure. I build the system in your stack, connected to your CRM, deploying AI where it creates leverage and keeping humans in the loop where judgment matters.
Activate
+The system goes live. Your reps start receiving AI-enriched, signal-scored accounts with context and recommended actions. I train your team on how to interpret AI-generated signal scores, how to prioritize outreach, and how to feed quality signals back into the system to make it smarter over time.
Optimize
+Signal quality is a living metric. I use AI to monitor which signals actually predict closed-won deals, automatically re-weight the scoring model, surface new signal patterns your team hasn't considered, and document everything so your team can maintain the system independently.
Signal Categories
Product Signals
Seat growth, feature adoption, usage patterns, activation milestones
Hiring Signals
New roles posted, department expansion, leadership changes
Financial Signals
Funding rounds, revenue milestones, budget cycle timing
Champion Signals
Job changes, promotions, new hires from your customer base
Competitive Signals
Competitor churn, tech stack shifts, contract renewals
Intent Signals
Content engagement, website visits, community activity
The real question isn't which signals to track—it's how to use AI to score them relative to your sales cycle and route them to the right person with the right context at the right moment. That's the 20% that changes everything.
The Work
Signal systems I've built and what happened.
Figma
Designed and deployed AI-powered signal workflows for Figma's GTM team, scoring over 300,000 product-qualified accounts (PQAs)—accounts showing real buying signals through product usage—across four dimensions: seat mix and growth, funding events, editor activity, and hiring signals. AI enrichment sourced from Snowflake, orchestrated through Clay, routed to sales with account-level context and recommended next actions.
Intercom
As GTM Engineering Lead, built the AI-driven infrastructure that moved Intercom's revenue team from manual prospecting to automated, intelligently enriched outbound at scale. AI-powered Clay enrichment pipelines feeding signal-scored accounts into prioritized rep workflows.
Kodex
Built a $33K AI-native signal engine covering agent searches, champion mobility, threat intelligence, job change monitoring, and new hire signals. HubSpot-Clay integration with AI-driven tier-based scoring for the law enforcement request management market.
Glytec
Salesforce data hygiene, AI-powered contact database growth for healthcare personas, and AI outbound infrastructure—delivered in a compressed sprint. Also built a reusable AI campaign-builder skill that uses Claude to systematize outbound creation going forward.
Starbridge.ai
Built the full AI-powered GTM context layer for a SLED procurement intelligence platform: documentation, AI tooling, and automation. Deployed 8 production AI tools. The kind of engagement where the client can maintain and extend everything after I leave.
The Process
Three steps between where you are and an AI-powered signal system.
The Signal Diagnostic
A free 15-minute conversation where I assess your current GTM signal infrastructure and AI readiness, then deliver three prioritized recommendations. Whether we work together or not.
The Build
If we're a fit, I design and deploy the AI-native Signal Architecture in your stack. Most builds take 4–8 weeks. You get a documented blueprint—including which AI agents handle which tasks—before I write a single workflow.
The Handoff
Your team owns the system. I train them on interpreting AI-generated insights, maintaining automations, and optimizing the signal model. I leave behind comprehensive documentation—because an AI system your team can't maintain without me isn't a system.
A note on how I work: I document everything. Architecture decisions, AI agent configurations, signal scoring rationale, integration logic, workflow dependencies—all of it. One client engagement produced a 59-file context repository. This isn't overhead. It's how I make sure the value extends far beyond the weeks I'm involved.
Get a GTM Signal Diagnostic.
15 minutes. I assess your current signal infrastructure, identify your three highest-leverage gaps, and deliver a prioritized action list—with a focus on where AI can create the most leverage in your GTM motion.
I'll also identify where AI fits into your company beyond GTM—starting with your go-to-market processes and fanning out from there into operations, enablement, and beyond.
No pitch. No obligation. If we talk and it's not a fit, you still walk away with a clear set of AI-ready next steps for this quarter.
Prefer email? hi@jeremyscottross.com
About
I'm a GTM Engineer based in Austin, Texas. I build AI-powered signal systems that help sales teams stop guessing and start knowing.
Before going independent, I was GTM Engineering Lead at Intercom, where I built the Clay-based automation that drove 140% pipeline growth. Before that, I designed signal workflows at Figma that processed over 300,000 product-qualified accounts. I've built bespoke AI signal engines for companies across SaaS, healthcare, law enforcement tech, and SLED procurement.
I'm obsessed with finding the places where AI and automation can replace manual, repetitive GTM work—and then actually building the systems that do it. Every engagement starts with the same question: what is your team doing today that an AI agent, a smarter workflow, or an automated pipeline could do faster, cheaper, and more accurately? I don't stop at the obvious answers.
I'm also building the GTM Engineering Apprenticeship because this discipline is too important to learn by accident.
When I'm not building signal engines, I'm probably experimenting in the kitchen, researching camping gear for the next family trip, or collecting terrible jokes to share with the kids in my life.
Education
The GTM Engineering Apprenticeship
The first structured path into GTM Engineering.
GTM Engineering is an emerging discipline, and right now most people learn it by accident—cobbling together skills from RevOps, sales, data engineering, and AI tooling until something clicks. The Apprenticeship compresses that timeline.
For Independent Professionals
You want to build a career in GTM Engineering. This track gives you the methodology, tool fluency, and portfolio to get hired or start consulting—without spending years figuring out what to learn first.
For Company Teams
You need GTM Engineering capabilities inside your org but can't hire fast enough. This track upskills your existing RevOps or growth team members into signal-literate, automation-capable GTM Engineers.
Applications for the inaugural cohort open soon. Join the newsletter to be notified first.
For fellow builders in the GTM space.
I'm always interested in conversations with people who are pushing the boundaries of how go-to-market actually works. If you're building tools, writing about GTM engineering, running a Clay agency, or teaching this stuff—I'd love to compare notes.
If you've been thinking about signal decay modeling, temporal vs. structural signal scoring, or how to adapt enrichment pipelines for vertical SaaS with 12+ month sales cycles—let's talk. These are the questions I haven't fully solved, and I'd rather work on them with someone sharp than alone.