GTM Systems Engineer AI-Driven Revenue

About GOARC

GOARC is an AI-native B2B SaaS company helping industrial organizations protect their people, improve frontline execution, and reduce operational risk.

Our platform brings intelligence, automation, and real‑time visibility to some of the most complex and high‑stakes operating environments in the world. GOARC helps companies move beyond reactive safety and operations management toward a smarter, more predictive, AI‑driven way of working.

The market opportunity is massive. Industrial companies are under pressure to modernize, improve safety performance, reduce risk, and operate with greater speed and precision. GOARC is built for that moment.

We have a clear industry‑leading offering, a wide‑open market, and a leadership team with a proven track record of building category‑defining companies. GOARC’s CEO and SVP of Revenue Operations have helped build two companies valued at more than $1 billion in this category.

For the right person, this is a rare opportunity to get in early, learn directly from proven leaders, and help build the next great AI‑native industrial SaaS company.

GoARC has strong demand and seasoned leadership that is personally running demand gen and outbound. What’s missing is the system underneath: the data, the automations, the content infrastructure, the AI workflows that turn a sophisticated sales motion into a compounding revenue machine.

That’s the job. You are part GTM strategist, part technical backbone of our revenue engine. You will design, ship, and continuously improve the systems, automations, and AI‑powered workflows that help our small, sharp go‑to‑market team operate at a level that looks impossible on paper. You will build the infrastructure that lets us scale without proportional headcount.

This is a high‑visibility, high‑ownership founding role. You will own the full go‑to‑market tech stack. You will work side by side with the CEO and head of sales. You will turn go‑to‑market from a set of disconnected tools into a cohesive, intelligent system.

• The trigger‑moment content engine. Structured intake of customer stories, transcripts, and field notes, transformed into an LLM‑readable repo that powers personalized outreach, case studies, and account‑specific assets at scale.
• The data and enrichment layer. ICP definition, data enrichment orchestration, intent and signal pipes (Linked In, news, hiring triggers, M&A), prospect list automation. The system the rest of GTM runs on.
• The outbound and follow‑on comms stack. Linked In (automated and CEO‑amplified), email sequencing, multi‑touch nurture, AI personalization layered over named‑account lists.
• The attribution and pipeline review. Dashboards the CEO can run in fifteen minutes a week. Source‑to‑revenue visibility. The truth, not vanity metrics.
• The internal AI workflow library. Claude Code, n8n, Make, or a similar iPaaS or agentic coding tool, MCPs and APIs wired into our stack so the team gets leverage out of every contact, every signal, every customer conversation.

A morning might be writing a Clay table that enriches a fresh list of plant‑level operations VPs across 200 process‑industry sites, wiring it into a sequenced campaign in Smartlead, and routing replies to the right person automatically. The afternoon might be sitting with the CEO turning a 45‑minute customer call recording into three field‑ready content assets and a templated case‑study draft.

The next day you might be debugging a Salesforce‑to‑Hub Spot sync, or shipping a Claude‑powered agent that drafts personalized Linked In messages off real‑time hiring signals, or rebuilding the pipeline dashboard so the weekly review takes 20 minutes instead of two hours.

You are hands‑on every day. You ship systems. You experiment quickly. You solve messy real‑world problems with software, AI, and judgment.

• Self‑starter. You see what needs to be built and you build it without being asked.
• 2 to 5 years in early stage B2B startups, ideally as one of the first GTM‑side hires.
• Hands‑on experience leveraging AI and LLMs in real workflows – Claude, OpenAI, agentic tools like Claude Code, not…