AI-Driven GTM Marketing Engineer

Bazeta

United States

Remote

USD 135,000 - 180,000

Full time

37 hours ago
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Benefits offered by this job

Equity
Benefits
Remote work

Job summary

Tremendous is a remote, high‑documentation company serving thousands of payouts. We seek a GTM Engineer focused on marketing to design AI‑driven workflows that automate high‑leverage marketing tasks.

You will work with brand, content, product marketing, paid, and events teams to deploy cross‑channel solutions. You must have 5–8 years in marketing operations, experience with LLM APIs and no‑code/low‑code tools, and a bias for rapid experimentation.

Qualifications

  • 5–8 years in marketing operations or GTM engineering.
  • Experience designing end‑to‑end campaigns and tracking channel performance.
  • Hands‑on with LLM APIs and workflow automation tools.
  • Comfort with APIs, webhooks, and basic scripting.
  • Ability to map workflows and identify breaking points before tool choice.
  • Demonstrated bias for rapid experimentation and iteration.

Responsibilities

  • Design and build agentic workflows across the campaign lifecycle.
  • Evaluate and deploy AI tools; run pilots and scale successful ones.
  • Create automated reporting pipelines for multi‑channel marketing data.
  • Develop AI‑assisted lead scoring and qualification with planners.
  • Enable marketers to run channel work via AI agents in tools like HubSpot.
  • Build reusable tools and workflows to speed up the team.

Skills

Marketing ops
GTM engineering
LLM APIs
Workflow tools
APIs
Webhooks
Scripting
Documentation

Tools

Zapier
Make
n8n

Job description

Tremendous is a remote, high‑documentation company serving thousands of payouts. We seek a GTM Engineer focused on marketing to design AI‑driven workflows that automate high‑leverage marketing tasks.

You will work with brand, content, product marketing, paid, and events teams to deploy cross‑channel solutions. You must have 5–8 years in marketing operations, experience with LLM APIs and no‑code/low‑code tools, and a bias for rapid experimentation.

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