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.What You’ll Do (aka Responsibilities)
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.)What You'll Bring (aka Education, Experience, Skills)
- Pursuing or recently completed a degree in computer science, engineering, data science, or a similarly technical field — or able to show equivalent self-taught technical ability
- Hands-on curiosity with LLMs like Claude, GPT, or Gemini — you’ve pushed past casual chatbot use and actually tried to build something with them
- Show us something you’ve built: a script, a bot, an automation, a class project, a weekend hack. It doesn’t need to be professional or polished — it needs to be yours, and you need to be able to walk us through it.
- Comfort reading and writing code (Python, JavaScript, or similar) and working your way through APIs and technical documentation
- A go-getter mindset — you chase down answers, ask questions early, and don’t wait to be told what to do next
- Willingness to learn fast in a space that changes month to month, and comfort being the person who figures it out
- Clear communicator who can explain technical concepts to non-technical marketing stakeholders without condescension
- Genuine interest in marketing and how a go-to-market team operates — prior marketing experience is not required
- Exposure to automation platforms (Zapier, n8n, or similar) or MarTech systems (CRM, marketing automation, analytics)
- Experience with multi-modal AI (image generation, video, audio synthesis) is a plus
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