AI Go To Market Engineer

Terminal Industries•Austin, TX

1d•Onsite

About The Position

At Terminal Industries, we believe the logistics yard is the last great untapped frontier in supply chain technology, a space still run on clipboards, radios, and guesswork. Yet these yards move the trucks, trailers, chassis, and containers that power global commerce. Every day, over $50 billion of goods move through more than 50,000 warehouses and medium- to large-sized factories in North America alone. Unlocking yard-level data is foundational to improving efficiency, sustainability, and scalability across the supply chain. That’s why we’re building the world’s first AI-powered Yard Operating SystemTM, a platform that digitizes, automates, and orchestrates everything that happens in the yard. Powered by our Terminal AI Computer Vision system and best-in-class machine learning, we give operators real-time visibility, intelligence, and control to slash dwell times, eliminate phantom costs, and boost throughput. The result? Safer, smarter, faster yards, and the chance to redefine a trillion-dollar industry from the ground up. Backed by top-tier investors and partnered with leading global logistics companies, we’re not just solving problems, we’re creating the category standard. Terminal is looking for a technical, commercially-minded AI GTM Engineer to build the automated revenue systems that let a lean go-to-market team operate like one several times its size. As the first hire in this function, this role offers significant potential for growth into a leadership position for the right candidate. Rather than throwing headcount at pipeline, you’ll architect and manage the systems that deliver results (data and process management, enrichment, scoring, signal detection, and AI-driven analysis and outreach that surface the right yard buyers and reach them at the right moment). Building this AI-powered engine well is pivotal to establishing Terminal as the undisputed leader in the industry.

Requirements

A builder’s instinct paired with commercial judgment, someone who treats go-to-market as a systems problem and is happiest building the machine rather than turning the crank.
Must be based in Austin, TX.
4+ years in a go-to-market, RevOps, growth, demand gen, or technical sales role where you built systems, not just ran plays, and you’ve been leaning into AI transformation for awhile.
Hands-on fluency with GTM automation and AI tooling — Salesforce, Clay, n8n/Zapier, Warmly, enrichment waterfalls, LLM-driven workflows, or equivalent — with a track record of shipping working automations. Bleeding edge user category.
Working comfort with data: SQL, APIs, and CRM data models, with experience in Salesforce.
Strong commercial bias: you reason about the ROI of your work and tie every build to pipeline, revenue, or efficiency.
An experimental, iterative mindset: you form hypotheses, test fast, read results honestly, and scale what works.
A bias toward learning by tinkering rather than waiting for perfect specs or a dedicated engineering team.

Nice To Haves

Experience in early-stage, high-growth, venture-backed startups.
Light coding ability (TypeScript, Python, Vibe) for custom integrations and scripts.
Experience standing up a GTM, RevOps, or GTM engineering function from scratch.
Familiarity with the modern GTM data ecosystem (Apollo, MAP systems, intent providers, reverse-IP, call-transcript tooling).
Domain experience in supply chain, logistics, or transportation technology — familiarity with the workflows of enterprise customers in these industries is a strong plus.

Responsibilities

Build and own Terminal’s GTM data foundation: keep our CRM (Salesforce for now) clean, deduped, and trustworthy through automated enrichment, schema hygiene, and clear ownership rules.
Design ICP models and propensity scoring for our market (yard operators, 3PLs, railroads, and shippers) so the team always knows which accounts to prioritize and why.
Build automated outbound and nurture systems that personalize at scale without sacrificing deliverability or quality.
Stand up signal detection: identify the firmographic, intent, and behavioral signals that predict a buy, an expansion, or a churn risk, and route them to the right person at the right time.
Prototype, test, and scale GTM plays end to end: write the spec, ship the workflow, measure the result, and template what works for the rest of the team.
Partner with Sales and Customer Success to automate manual work (account research, CRM updates from call transcripts, follow-ups, QBR prep) so they spend their time selling and retaining.
Own the GTM tooling stack (Clay, enrichment providers, sequencers, CRM, integrations) and make sound build-vs-buy calls as the function matures.
Measure yourself on outcomes: meetings booked, pipeline created, and hours given back to the team.
We’ve done much of the work regarding ICPs, personas and routes to market, you’ll bring it all together.