AI Workflow Engineer

Serotonin•Los Angeles, CA

1d•$80,000 - $190,000•Remote

About The Position

We are building the AI layer across Serotonin's marketing operations. This role sits at the intersection of systems thinking, AI tooling, and marketing execution. You will move across our marketing teams spanning PR, content, growth, social, and design, not to go deep on one team's problems, but to find the friction points that show up everywhere and build things multiple teams can pull from. Your job is to understand how those teams work before you ever open a tool. That means asking the right questions, shadowing stakeholders, mapping actual workflows, and identifying where things slow down. The best outcome is never a custom fix for one person. It's something three teams are running independently six months from now. This role is best suited for someone who listens to a team for 30 minutes, draws a process diagram, identifies the friction point, and ships a working solution within a week. You will work directly with marketing leads and internal and external client teams, translating real workflow problems into outcomes that scale across the organization.

Requirements

The most important thing is how you approach a problem. You should be the kind of person who interviews the full team before proposing a solution, is able to map a workflow end to end after a few conversations, and gets more satisfaction from making someone else's work easier than from showing off what you built. You think in systems that serve multiple stakeholders at once. When you build something for the content team, you are already thinking about how the PR team will use a version of it next month.
On the technical side: strong prompt engineering across the major LLMs, hands-on experience with workflow automation tools like Make, Zapier, or n8n in a real production context, and enough comfort with APIs and JSON to connect things when there's no native integration. Familiarity with the broader martech stack and AI creative tools matters too, but these are learnable.
You should understand how a marketing team operates at the foundational level, in regards to how the PR, content, growth, and social teams actually function day to day. Knowing the difference between a campaign brief and a distribution workflow, and why that matters when you're designing an AI system around it.
Crypto or Crypto marketing experience is a real plus, but not required.

Nice To Haves

Doesn’t care about rigid job titles: is equally comfortable acting as a strategist, a builder, a trainer, or an operator depending on what the problem demands
Loves tinkering and experimenting with new tools before anyone else has heard of them: and has the judgment to know which ones are worth deploying at scale
Gets energy from hard, ambiguous problems: not from following established playbooks, but from writing the new ones
Ships fast and isn’t precious about being wrong on the first try
Wants to see their work create real client impact: not just live in a deck or a Notion doc that nobody reads
Believes AI is a multiplier, not a shortcut: and builds workflows that reflect the difference
Thrives in a fast-moving, globally distributed team where autonomy is high and there’s no one to hand the problem off to

Responsibilities

Diagnose Bottlenecks - spend real time with our different core marketing teams before touching any tooling. Interview team members, map how work actually moves, and identify where things slow down or break.
Design & Build for Multiple Teams - build the workflow systems to solve them. That means AI-powered workflows, content and campaign pipelines, and no-code automations that connect into the tools teams already use: HubSpot, Notion, Slack, various native social platforms.
Workforce Adoption - You will own the operational backbone that makes AI adoption stick across a 90-person global team: prompt libraries, SOPs, workflow playbooks. You will be responsible for leveling up the AI proficiency across the team.
Maintain & Scale - Work directly with internal & external client teams to diagnose GTM bottlenecks and build AI-assisted solutions, from content at scale to campaign automation to research synthesis.
Upleveling - Evaluate, test, and onboard tools as the landscape shifts. Define how we measure impact: time saved, output quality, client adoption, etc and build reports around what is working and what isn't.