Big Tech’s Layoff Meltdown, Explained

Over the last year, hiring teams have started seeing a wave of new job titles pop up across tech, sales, and operations.

Some are legitimate new roles.

Others are existing jobs with a slightly different name.

And many of them have one thing in common: AI is suddenly part of the job description.

From Go-to-Market Engineers to AI Specialists, companies are experimenting with new roles as they figure out how automation and AI fit into their teams.

But most of these positions aren’t entirely new. They’re evolutions of existing roles.

The Rise of Go-to-Market Engineers

One role that’s gaining traction is the Go-to-Market Engineer.

Depending on who you ask, it’s either:

• A new role focused on automation and AI-driven growth
  
• Or a modern version of Revenue Operations (RevOps)
  

In practice, it’s a bit of both.

We recently worked on a role called an Outbound & Go-to-Market Specialist. Instead of traditional RevOps work like reporting and CRM management, the focus was on:

• Building AI prompts
  
• Creating campaign messaging
  
• Automating outreach workflows
  
• Using tools like Clay, Smartlead, and Trigify
  

The goal wasn’t just managing sales data. It was accelerating pipeline generation through automation.

In other words, the role was designed to help SDRs and AEs move faster.

AI Isn’t Creating New Functions. It’s Changing Existing Ones

One trend is becoming clear: companies aren’t replacing entire departments with AI.

Instead, they’re changing how existing roles operate.

Sales teams still need pipeline.

Marketing teams still need content.

Engineering teams still need to build software.

The difference is that employers now expect candidates to use AI tools as part of the workflow.

That’s why we’re seeing so many job titles that start with “AI.” But that may not last forever.

Why Many “AI Job Titles” May Disappear

Right now, AI still feels new enough that companies highlight it in job titles.

But eventually, AI will likely become a baseline expectation, not a specialty.

Think about it like cloud technology or data analytics.

At first, companies hired “cloud specialists.” Now most engineers are expected to understand cloud infrastructure.

The same shift will likely happen with AI.

Instead of hiring “AI-enabled marketers” or “AI engineers,” companies will simply expect employees to know how to work with AI tools.

The Talent Pool Is Still Small

One challenge with these emerging roles is simple: there aren’t many candidates with real experience yet.

Many of these positions didn’t exist two years ago.

In one recent search, we started looking for a candidate locally in Chicago. Eventually we expanded nationwide because the pool of people with relevant experience was extremely limited.

This is a common issue with emerging roles:

• Companies want experienced candidates
  
• But the roles themselves are still new
  

That gap will likely persist for the next few years.

Hybrid Roles Are Becoming More Common

Another noticeable shift is that roles are becoming more hybrid.

Instead of hiring for narrow responsibilities, companies are combining multiple functions into one position.

For example:

Forward Deployed Engineers

A model popularized by Palantir, these engineers:

• Work directly with clients
  
• Gather product requirements
  
• Write user stories
  
• Build the software themselves
  

That used to involve several roles: product managers, engineers, and solution architects.

Now, AI tools allow one person to cover more ground.

Similar changes are happening in other functions as well:

• Finance roles are shifting from manual processing to analysis and reporting.
  
• Data analysts are being asked to handle architecture and data pipelines.
  
• Accounts receivable roles are becoming AR analyst positions focused on insights rather than data entry.
  

Automation removes repetitive tasks, leaving more strategic work behind.

What This Means for Hiring

For employers, the takeaway is straightforward.

Job descriptions need to evolve alongside technology.

Instead of focusing only on traditional experience, hiring managers should consider:

• Candidates who have learned new tools quickly
  
• People with automation and systems thinking
  
• Talent who can combine multiple skill sets
  

Because in many cases, the perfect candidate with the exact title simply doesn’t exist yet.

The Bigger Trend

We’re currently in a transitional phase in hiring.

AI is changing how work gets done, which means job titles, responsibilities, and expectations are shifting quickly.

But most of these “new” roles aren’t entirely new professions.

They’re existing jobs adapting to new technology.

And as companies continue experimenting with AI, the titles may keep changing.

The work itself, however, is likely to look familiar.