What Do You Call Yourself When the Job Doesn’t Exist Yet?
The surprisingly liberating frustration of being early to a field that hasn’t named itself.
I’ve updated my LinkedIn title four times in the last six weeks.
Four times. Which, if you know me, is both completely on brand and also slightly mortifying. Each time I change it, I feel a small flicker of yes, that’s closer — followed immediately by the nagging sense that it’s still not quite right. Not because I don’t know what I do. But because the market doesn’t have a clean word for it yet.
And if you’re a designer, a systems thinker, or anyone who has spent the last year trying to position yourself in the AI space without an engineering degree — I have a feeling you know exactly what I’m talking about.
The Job Search, Honestly
Here’s what actually happens when I search for roles right now.
I type “AI” into LinkedIn. I get engineers. Senior ML engineers, AI architects, LLM specialists, full-stack developers building agentic pipelines. Brilliant people. Not my lane.
I type “UX Designer.” I get... traditional UX. Figma wizards, product designers, research leads. The roles are real. But increasingly, they’re splitting into two camps: UX-plus-engineering on one side, UX-plus-product-management on the other. The space where I’ve lived — complex systems, enterprise workflows, defense applications, human-centered design for genuinely high-stakes environments — is quietly disappearing from the posting boards as its own category.
I type “AI Solutions.” I get one job.
ONE.
Out of thousands of postings. A role called something like “Agentic AI Solutions Lead.” Enterprise systems. Non-technical. Someone who understands how AI agents actually need to function alongside humans — designing the trust layer, the governance framework, the workflow architecture. Reading it, I felt the specific, electric recognition of that’s it. That’s what I’ve been building toward.
One posting. In the entire country. Right now.
What This Tells Me (Once I Stopped Being Frustrated)
My first reaction was honestly just... defeat. I’ve spent the last year going deeper into this space than most non-engineers I know. Through the Maven course and my own obsessive R&D, I’ve built agents, designed multi-agent orchestration models, written governance frameworks and evaluation systems. I understand RAG architecture well enough to design around its limitations. I have a DoD Top Secret clearance and years of experience designing mission-critical enterprise systems for Air Force operations.
And here’s the part I used to be embarrassed about, but I’m not anymore: one of those projects never reached the operators it was built for. Eight years of contract work (I was on it for almost five), cancelled before users ever touched it in full operation. I used to treat that as a gap on my resume. Now I think it’s the clearest evidence of exactly what I keep writing about. When the human integration layer — the trust design, the ‘how do actual people use this under pressure’ layer — isn’t built into the foundation from day one, eventually someone notices. Sometimes it’s eight years in.
And I couldn’t find my own job posting.
But then I sat with it longer. (Classical music in the car, obviously.) And something shifted.
The reason I can’t find the job is not that I’m wrong about the direction. It’s that I’m early.
These are genuinely different things. And it took me longer than it should have to stop confusing them.
Being Early Isn’t the Same as Being Wrong
Think about every role that exists in tech today and feels completely obvious and necessary.
UX Designer. Didn’t exist as a job title until the late 1990s. Product Manager — the modern version — barely existed before the 2000s. Data Scientist became a “real” job title around 2012. Before that, people were doing the work without the title, or being called something adjacent that didn’t quite fit, or being hired under a job description written by someone who didn’t fully understand what they needed yet.
Every one of those roles was, at some point, the job that didn’t exist yet.
The people who defined those roles didn’t wait for the posting. They did the work, built the language around what they were doing, and became the definition.
That’s what’s happening right now in the human-AI collaboration space. The work exists. The need is real and growing and urgent — and everything I’ve spent the past year immersed in, from the Maven coursework to the case studies to the practitioner accounts I’ve followed closely, points to the same pattern: enterprise after enterprise is deploying AI systems with careful thought given to the interface — and almost none given to how the humans alongside those systems will actually function, trust them, catch their mistakes, or override them when necessary. Designers are already doing valuable work naming AI Design System Patterns at the UI layer. But the collaboration layer — the trust architecture, the governance framework, the human-AI workflow design — is still almost entirely undesigned. That gap is enormous. And it is absolutely going to be somebody’s job to fill it.
The posting just hasn’t been written yet. Or rather — it’s being written in real time, by the handful of companies who are far enough ahead to know they need someone like me.
The posting just hasn’t been written yet. Or rather — it’s being written in real time, by the handful of companies who are far enough ahead to know they need someone like me.
So What Am I Calling Myself?
For now — and I want to be honest that “for now” is doing real work in that sentence — I’ve landed on something that feels like the best current approximation:
AI Solutions Lead | Enterprise Workflow & Systems Design
On LinkedIn, I’m leading with: AI Workflow & Systems Design | Human-AI Collaboration | Enterprise Agentic AI | DoD TS Cleared
In conversations, I skip the title entirely and just say: “I design how humans and AI agent teams actually work together in enterprise environments — the trust layer, the governance framework, the part that makes the whole thing usable for real people making real decisions.”
That version always lands. Every single time. Because the need is obvious the moment you describe it out loud. The title just hasn’t caught up.
On my Substack — where I get to be slightly more honest about where all of this is actually heading — I’ve been calling myself an AI-enabled Enterprise Systems Thinker. Which is accurate. And also sounds like something I invented at 11pm driving home from nowhere. (I did.)
None of these feel permanent. All of them feel true.
The Part That’s Actually Kind of Exciting
Here’s the thing I keep coming back to, underneath the frustration.
The people who are early to a field that’s still naming itself get to help name it. The frameworks being built right now for how humans collaborate with AI agents — for how trust works, for how governance gets designed, for what “human in the loop” actually means in practice rather than just on paper — those frameworks don’t exist yet in any standardized form. The people building them, writing about them, developing the methodology while the market catches up?
They become the reference point.
I’m not saying that to be grandiose. I’m saying it because it’s the thing that gets me out of bed on the days when the job search feels like shouting into a void. The void is temporary. The work is real. And the moment the market language catches up — which it will, faster than any of us expect — the people who were already there, already doing it, already writing about it?
They won’t have to explain themselves.
I’m writing this series for anyone else in that in-between space. The designers who know they’ve outgrown the old title but can’t find the new one yet. The systems thinkers who don’t fit cleanly into engineering or product. The people who are doing work that matters and just need the world to develop the vocabulary for it.
You’re not lost. You’re early.
There’s a difference.
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What are you calling yourself right now? I’d genuinely love to know — drop it in the comments. And if you’re building something in this space and looking for someone who can design how the humans work alongside your AI systems, I’d love to connect.
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In the spirit of transparency I always advocate for: I worked with Claude to structure and shape these thoughts. The four LinkedIn title changes, the one job posting, and the car-drive realization are entirely, painfully, mine.
