Tech Hiring Right Now: What the Data Actually Says (And Where the Jobs Still Are)
If you strip away the headlines and hot takes, the tech job market is pretty simple right now:
Layoffs are still high
Hiring is tighter than it used to be
AI-related roles are growing fast
Everything else is more competitive
That’s it. No fluff needed.
The Reality in Numbers
Here’s what matters right now:
~120,000+ tech layoffs already in 2026
April was one of the worst months in the past 2+ years
Thousands of open roles have been quietly pulled back (not filled)
Most large companies are backfilling selectively, not growing headcount
At the same time:
Billions are being poured into AI infrastructure
New AI startups are raising aggressively
Demand for specific technical roles is still strong
So yes — fewer jobs overall.
But also: very real demand in specific areas.
Where Hiring Is Actually Happening
Let’s be specific. The demand isn’t evenly spread — it’s concentrated.
1. AI / ML Engineers
Still one of the hardest roles to fill
Strong compensation, even in this market
Especially valuable: applied AI (not just research)
2. Product-Oriented Engineers
Engineers who can ship features, not just write code
Bonus if you’re using AI to speed up output
3. Data + Infrastructure
Data pipelines, ML ops, infra scaling
The “behind the scenes” work powering AI products
4. Cybersecurity
Demand hasn’t dropped
Still a priority spend across companies
Where Things Are Slower
This is where people are feeling it:
Mid-level software engineers (generalist)
Recruiters and talent teams
Customer support / operations roles
Non-technical roles inside tech companies
These aren’t gone — just:
More applicants
Fewer openings
Longer hiring cycles
What’s Changed (Without Overcomplicating It)
A few clear shifts:
Teams are smaller
Companies are not hiring the way they were in 2021–2022.
You’re expected to do more.
Open roles ≠ real hiring
A lot of postings aren’t urgent. Some aren’t even active.
AI is already affecting workflows
Not in a “replace everyone” way — but enough to:
Reduce hiring needs
Increase expectations per person
What Candidates Should Actually Do
No theory — just practical adjustments.
1. Show how you use AI (even if you’re not “in AI”)
You don’t need to be an ML engineer.
But you do need to show:
How you use tools to move faster
How you automate parts of your work
How you increase output
If you’re not talking about this, you’re blending in.
2. Be more specific about what you do
“Software Engineer” isn’t saying much anymore.
Better:
What do you build?
What problems do you solve?
What kind of teams do you work on?
Specificity cuts through competition.
3. Assume every role is competitive
Even strong candidates are:
Applying more
Interviewing longer
Getting fewer responses
That’s normal right now. Adjust expectations accordingly.
4. Focus on companies that are actually hiring
Not just brand names.
Look for:
AI-focused startups
Profitable companies
Teams tied to revenue or core product
That’s where hiring is still happening.
5. Have proof of work
This matters more than it used to.
Examples:
Projects
GitHub activity
Case studies
Anything that shows output
Resumes alone aren’t carrying people right now.
The Bottom Line
The market isn’t great — but it’s not dead either.
There are fewer opportunities overall.
But there are still very real opportunities if you’re aligned with where demand is.
Right now, that mostly means:
Technical depth
Ability to ship
Comfort using AI tools
Everything else is just more competitive than it used to be.