I was at a hackathon back in January when I met someone who introduced themselves as a Forward Deployed Engineer (after saying their name, of course).
I stared at them for a bit before asking: what does that mean?
After they explained it (and after I quietly looked up the job description on their company's website) I worked out that they were part consultant, part software engineer.
A whole job out of that? I'd always assumed it took a team: someone to talk to the users, someone else to build the thing. Now it's a one-man show. And it seems to be a pretty popular job at the moment, because I keep seeing it everywhere.
That interaction got me thinking about my own job titles. I applied to be a Learning and Research Intern at Taught by Humans in 2025, got put forward for a Data Content Developer Intern position instead. Fast forward to now, I'm a Founder's Associate Intern.
Once again: what do any of those even mean?
I thought extravagant titles might've been a tiny startup thing. Turns out they're not. Anthropic had over 400 job openings and my boss, Laura, reckons she understands maybe 20 of them (even though she's had 10 years of experience in the AI field).
Job titles like Software Developer or Accountant land instantly. But introduce yourself as an Applied AI Technical Evangelist, Startup Ecosystem for Anthropic and you've lost the crowd there. It seems like a lot of companies are making jobs up as they go, as and when they need them. There seems to be less standardisation in job roles now.
So, How Are You Meant To Find Anything?
When I told Laura about all this, she gave me the simplest but best piece of advice I've had: ignore the titles and read the job description.
This worked brilliantly at first. During my graduate job hunt I had a list of roles I was interested in and companies I wanted to apply to. Reading the descriptions meant I could tell when a data scientist job was really more of an analyst role and vice versa (which saved me a lot of confusion when applying).
The trouble started when that list ran out and I was heading into my exploration phase. The problem is: most platforms (LinkedIn, Indeed, Glassdoor) still mainly filter by job title. So I couldn't read the description for a role I couldn't find. And I couldn't find it, because I'd never heard of it and didn't know its name. The best advice I'd been given was the one thing the search bar wouldn't let me follow.
Then it clicked why Laura's advice worked in the first place. By reading the description, I was doing skills-matching on my own. I was scanning for things I actually had (like working knowledge of Python or basic SQL) instead of guessing at what a role might be called.
Unfortunately, you can't just type niche data jobs across different industries into Indeed and expect a whole list of roles you've never heard of. But I discovered a neat little way around it: using Dotly. Dotly is our platform's learning companion, and one of the (many) things it does is careers coaching.
I fed Dotly all of my skills and asked for job recommendations beyond the ones on my list. It came back with job titles I'd never have thought to search for, like Data Quality Engineer or Data Journalist.
Dotly recommends data career options tailored to the user's listed skills.
I even got Dotly to pull up live roles I could actually apply for.
Conversation where Dotly presents live listings for data-related jobs.
As I'm looking for entry-level roles, though, the supply did seem limited and focused on bigger grad schemes. For Laura and Amy, who are both experienced in their fields, Dotly gave plenty of listings that matched their skills. Perhaps it's just not the season.
While it isn't a live job board with skills-matching, it's still a pretty good fix (and definitely better than the Indeed search bar).
Job titles aren't going to get any simpler. Year by year they'll keep mutating into things we've never heard of. But as long as we change how we search, matching on skills instead of job titles, Anthropic can invent another 400 roles and it won't faze us.