Founding GTM Engineer, Trunk Tools

• AI-pilled and fluent with the frontier - you use the latest models, tools, API calls, and MCPs daily, and you know how to turn them into working automations
• Strong business sense - you can dive into a real-world GTM problem, reason about tradeoffs, and figure out what actually moves the needle
• Exceptional communication - you frame problems clearly, explain your thinking crisply, and translate between technical and commercial audiences
• A builder's instinct for workflow automation and tool development - you go from a messy business problem to a working system fast, without waiting for a playbook
• A product mindset: able to prioritize, scope, and ship the right thing for internal "customers" across GTM
• Comfort in a fast-paced, ambiguous, execution-focused environment where you own outcomes end to end

Desirable

• Trunk Tools is hiring its first Founding GTM Engineer to build the workflow automation and AI orchestration that powers our entire go-to-market funnel
• You'll sit at the intersection of product, sales, marketing, customer and engineering - acting less like a traditional operator and more like a systems engineer for revenue generation
• This person will design and own the internal "AI operating system" that all of GTM at Trunk runs on: the automated workflows and the AI-agent layer that turn repeatable manual work into systems
• This is a builder role with an outsized amount of ownership
• In many ways it's a pseudo- internal PM position: you'll decide what to build, prioritize across GTM functions, and ship the tooling the whole org depends on
• It's deeply technical - you should be as capable as a strong software engineer - but the best person for it is also curious about the commercial side and, ideally, brings GTM strategy or ops experience of their own
• This is a founding seat: you'll be part of building the highest-leverage GTM ops team in the AI space
• The GTM AI OS, end to end: treat the internal GTM toolset as a product. Gather requirements from GTM leaders, prioritize across functions, build, ship, measure, and iterate - the AI operating system the whole org runs on
• Workflow automation across the full funnel: build systems that take an account from raw signal through enrichment, scoring, routing, and outbound orchestration with no manual steps in between - and extend the same automation into post-sale handoffs
• AI orchestration: build and own the AI-agent layer - internal agents for account research, personalization, qualification, call summarization, and analysis at scale. You'll reach for LLMs and agents as core infrastructure, not novelty
• Data architecture & pipeline (co-owned): you'll have a real hand in the GTM data foundation and pipeline that everything else runs on. This is co-owned with engineering and a planned data-engineering hire - you shape and depend on it, but you won't carry it alone
• Stack ownership: evaluate new tools, manage vendor relationships, and recommend stack changes as we scale
• ---What the first 90 days look like---
• Map the current GTM stack and the manual workflows the team runs today, and ship one or two visible automation quick wins
• Stand up the first end-to-end automated workflow: signal → enrichment → scoring → routing
• Layer in the first AI-orchestration step - an internal agent for research, personalization, or summarization
• Partner with engineering and the data-engineering hire on the shared data foundation underneath it all
• Publish a prioritized roadmap for the GTM AI OS, with early wins measured against our two anchor outcomes: demand / pipeline generation and attribution, and quote-to-cash optimization