When Evaluating Candidates, How do you Seperate the Pretenders from the Real Thing? – featuring Affirm

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 is gaining traction is the Go-to-Market Engineer.

Depending on who you ask, it is either:

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

In practice, it is a bit of both.

As Matt Tokarz recently pointed out after closing a search for an Outbound & Go-to-Market Specialist, the role looked very different from traditional RevOps. The focus was not reporting or CRM hygiene. It was building prompts, leveraging tools like Clay and Smartlead, and enabling SDRs and AEs with backend insights to accelerate pipeline growth.

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 was not simply managing sales data. It was accelerating pipeline generation through automation.

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

One trend is becoming clear. Companies are not replacing entire departments with AI.

Instead, they are 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 their workflow.

As Zac Colip noted during the discussion, we are currently in a transitional phase where companies are labeling roles with “AI” as they experiment with how the technology fits into teams.

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.

As Matt Mulcahy highlighted, one example is the rise of Forward Deployed Engineers, a model popularized by Palantir.

These engineers:

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

What used to involve several roles, including product managers, engineers, and solution architects, can now sometimes be handled by one person. AI development tools are part of what makes this possible.

AI Adoption Is Happening at Different Speeds

Not every industry is moving at the same pace.

As Ashley DuBois pointed out, some sectors, such as transportation, are applying AI to specific workflows like load booking and operational automation.

At the same time, some companies are adding “AI” to job titles even when the core responsibilities remain largely traditional.

In many cases, it is still essentially an IT manager role with AI familiarity layered in.

This reflects a broader transition period where companies want to signal modernization and candidates want to signal relevance.

Automation Is Changing Operations Roles

In logistics, AI is increasingly handling scheduling, tracking, and coordination tasks.

According to Brittany Lasky, operational roles such as logistics coordinators may experience the greatest impact from automation.

However, freight brokers who manage negotiation and strategic RFPs remain in demand.

AI can optimize processes. It does not replace relationship management or strategic negotiation.

Across industries, a pattern is emerging.

Execution becomes automated. Strategy becomes more valuable.

Finance Roles Are Becoming More Analytical

Automation is also reshaping finance and accounting roles.

As Adam Slater noted, accounts receivable jobs that once focused on high-volume manual processing are evolving into more analytical positions centered on reporting and insights.

The work is not disappearing. The expectations are increasing.

Organizations are now hiring for:

• stronger technical skills
• analytical thinking
• systems understanding
  

Even roles traditionally considered administrative now require deeper technical capability.

Analyst Roles Are Expanding

AI is not eliminating analyst roles. It is expanding them.

Michelle Mehlis pointed out that many data analyst roles now include responsibilities previously handled by data engineers or architects.

Financial analysts are also expected to understand tooling, sourcing, and data transformation.

In many cases, two or three roles are being combined into one.

This raises a long-term question.

If entry-level roles become more complex or disappear entirely, how will organizations develop senior talent in the future?

Sales Development Is Becoming More Human

The traditional model of high-volume cold calling is changing.

According to Jack Smith and Emily Canna, teams are shifting toward:

• personalized LinkedIn videos
• voice memos
• highly tailored messaging
  

At the same time, companies are moving away from activity-based KPIs and focusing more on outcomes such as demos set and SQLs generated.

In a market saturated with automated outreach, authentic communication has become a competitive advantage.

Several clients have said it directly. They want a human in the seat.

Go-to-Market Teams Are Rebuilding the Fundamentals

Every six to twelve months, hiring trends in go-to-market teams shift.

As Jennifer Salerno noted, companies move through cycles.

One quarter it is BDRs.
Then RevOps.
Now it is go-to-market engineers.

Many companies experimented heavily with AI to accelerate pipeline generation.

What those experiments exposed were structural gaps, particularly in outbound strategy.

AI can support execution. It does not replace a well-built top-of-funnel engine.

Inbound momentum can hide weaknesses. Outbound forces clarity.

The companies gaining traction right now are not chasing trends. They are rebuilding the fundamentals of their go-to-market strategy.

What This Means for Hiring

For employers, the takeaway is straightforward. Job descriptions and expectations need to evolve alongside technology.

Across functions, we are seeing the same shift play out. AI is not eliminating entire roles. It is changing how those roles operate and increasing the baseline skill set required to perform them well.

Hiring managers should start thinking less about traditional titles and more about capabilities. That often means prioritizing candidates who can:

• Learn and adapt to new tools quickly
• Think in terms of systems, automation, and workflows
• Combine technical and business skills within a single role
  

In many cases, the perfect candidate with the exact title simply does not exist yet. The strongest hires are often people who have developed adjacent skills and shown the ability to adapt as the tools evolve.

The Bigger Trend

The broader trend is that AI is accelerating a shift that was already underway.

Roles are becoming more hybrid. Expectations are increasing across nearly every function. And repetitive tasks are being automated, leaving more strategic work behind.

Sales teams still need pipeline.
Operations teams still need coordination.
Finance teams still need reporting and analysis.
Engineering teams still need to build software.

What is changing is how the work gets done and what skills are required to do it well.

Right now we are in a transitional phase where companies are still labeling roles with “AI” as they experiment with new workflows and technologies.

Over time, that label may disappear.

AI will simply become part of how work gets done.

And the roles themselves, while evolving, will look more familiar than the titles might suggest.