Agentic Marketer

Every wave of technology creates a job that did not exist before it. Print made the brand storyteller. Digital made the funnel marketer. Product-led growth made the growth hacker. AI is making the next one, and it is not “a marketer who is good at ChatGPT”.

It is the person who sits with a commercial team, sees how the work really flows, and then designs the system that does the repetitive part for them. Agents, data, a bit of code and a lot of taste. We call that person an Agentic Marketer.

Nobody has five years of experience in this job. Two years ago the tools that make it possible did not exist. So we are not looking for a CV that fits a box. We are looking for the few people who started doing this job before anyone gave it a name.

Why this job exists now

There is a lot of noise about the marketing jobs AI will take. We see the opposite. AI is killing the tedious part of commercial work and making the thinking part worth more. Here is our take:

1. There is no ceiling on commercial work. Every company wants more content, more pipeline, faster follow-up and better answers for its customers. So there is no ceiling on what is worth automating.
2. Building the agent is no longer the hard part. With today’s tools, a good team ships in days what used to take a quarter.
3. Knowing what to build still is. Which workflow quietly leaks revenue. Which “simple” handover touches marketing, sales and finance at once. Which number actually means something. And how to get a team that has been burned by tools before to trust a new one.
4. That takes a marketer who has done the work. Someone who has sat in the meetings, felt the pain, and can now design the system that removes it.

AI is about to make average marketing very cheap. The person who decides where to point it gets more valuable, not less. That is this job.

You might already be this person

• You automated a chunk of your own job, then got restless because the rest of the team still works the old way.
• You have a Make or n8n account, a folder of prompts, or a Claude project you are a little too proud of.
• When someone says “the leads are bad”, you want to read the call transcripts, not the dashboard.
• You have written a creative brief and thought: this would be clearer as a spec an agent could run.
• You have watched a good campaign die because the handover between marketing and sales was nobody’s job.
• You care about qualified replies and pipeline, and you get twitchy when someone reports impressions.
• Salespeople and engineers both take you seriously, which surprises them more than it surprises you.

If three of these made you smile, keep reading. Whether you have five years in marketing behind you or fifteen, this is probably the job you have been doing on the side.

What you will actually do

You are embedded with our clients’ marketing, sales and customer support teams. You own the line from “we should do something with AI” to a system that is live, trusted and moving a number.

• Sit with the team. Run discovery and workshops, shadow the work, read the CRM notes and the support tickets. Find where time and revenue leak.
• Decide what is worth building. Rank opportunities on business value, feasibility and how ready the team is. Say no to the shiny ones.
• Write the spec. Turn a messy workflow into an agent job spec: inputs, triggers, filters, output standard, human approval and the one metric that matters.
• Build it with the engineer. Prototype where you can, test assumptions early, and make the scope calls that keep a project shippable.
• Run the delivery. Plan, budget, dependencies and honest updates on trade-offs, for decision-makers and users alike.
• Get it used. Plan acceptance, training and handover with the people who will live with it. An agent nobody trusts is a cost, not a system.
• Measure, then go again. Review results after launch, report pipeline instead of activity, and find the next workflow worth fixing.

On a Monday you might run a workshop with a client’s sales director. By Thursday you are reviewing an outbound agent’s drafts with our engineer and cutting the half that still sound like a robot.

Who you work with

You work side by side with an AI Engineer. You own the why and the what; they own how it holds up in production. The best work happens in the space between, so you will argue well in both directions.

Agentique is a small team where business analysts, marketing experts and AI engineers sit together. The gap between the people who understand the business and the people who can build is a desk, not a department. You report directly to the founder.

What you bring

• Solid years in marketing, growth, sales ops or RevOps, in-house or at an agency, close to real numbers.
• Hands-on time building with AI and automation tools. You do not need to be a developer, but you can read an API doc, work with data and explain what a model cannot do.
• At least one initiative you led from the first conversation to a live result, including the plan and the budget.
• Commercial judgement: you can build a credible case for why a workflow should change.
• The backbone to tell a director their expectation is unrealistic, and keep the relationship.
• Clear writing and speaking, for engineers and executives alike.

This is not for you if

• You want a job description that stays the same for three years.
• You would rather manage the people who do the work than design the system that does it.
• You see AI as a content factory. We build the opposite.
• You prefer presenting the strategy to seeing it ship.

Why here, why now

Most companies are still copy-pasting out of a chat window. The window to build the compounding version of commercial work is open right now, and it will not stay open long.

Here you get to define what this job is, in Belgium, before most people know it exists. You will shape what we build, how we deliver it, and which products come next. If our piece on the rise of the marketing engineer made you nod along, this is that job, done for many companies at once.

Interested?

Skip the cover letter. Send your CV or LinkedIn profile and tell us about one thing you built or automated: what you chose to fix first, which trade-off hurt, and how you knew it worked.