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United States
Remote only
As our Marketing AI Intern, you’ll help the marketing team work faster and smarter with AI. You’ll sit with the team and build the things that remove busywork — custom AI agents, automated workflows, and small internal tools. You don’t need to have done this job before. You need to be technical enough to pick it up quickly, and driven enough to keep going when the documentation runs out. We’ll teach you the marketing side. You will report to the Sr. Director, Marketing Operations.
This is a 4-month, full-time, contract role. You’ll be embedded with the marketing team from day one, working through a real backlog of AI projects on a daily cadence. This is a build role, not a shadowing role — expect to ship things people actually use.Build AI Agents Build and improve custom AI agents and agentic workflows (using Claude, OpenAI GPTs, and similar platforms) that help specific marketing roles — field marketing, content, digital marketing, and marketing operations. You’ll collect feedback from the team and keep iterating.
Workflow Automation Learn tools like Zapier, MCP connectors, and LLM integrations, then use them to wire AI into our existing martech stack (Marketo, Salesforce, 6sense, and more), replacing manual steps with automated ones.
MCP Connectors Help build and maintain Model Context Protocol (MCP) connectors across our marketing applications. MCP is how we give AI tools secure, structured access to our systems — we’ll teach you how it works, and you’ll own pieces of it as you ramp.
Prompt Engineering Help build a shared library of prompts, skills, and brand voice frameworks so AI output stays consistent across the team, and help document the guardrails for how we use these tools.
Backlog Delivery Work through projects from marketing’s AI backlog and ship something useful most weeks. Momentum and follow-through matter more here than polish.
Enablement & Office Hours Help run office hours and walk teammates through new tools. A lot of the value in this role comes from sitting next to someone and unblocking them.
Sharing What Works Document and share what you learn — what worked, what didn’t, and what’s worth trying next — so the whole team gets better, not just you.
Tool Evaluation Explore and evaluate AI tools and give an honest read on whether they’re worth adopting, keeping our data security and integration standards in mind.
Stretch Projects If you’re moving fast, there’s room to go deeper — Retrieval-Augmented Generation (RAG), multi-modal AI, or more ambitious agent designs. (Nice to have, not expected.)
