I Applied to 106 Software Engineering Jobs in 2026. Here's What Happened.

96 days, 106 applications, one offer, and a hiring process that occasionally seemed to disagree with itself.

After spending 12 years at the same company, I found myself back on the job market in 2026.

With over 20 years of software engineering experience, a background in architecture, cybersecurity, distributed systems, and more recently AI-assisted development, I thought I had a reasonably competitive profile.

Apparently, the job market had other plans.

Once my search was over, I decided to reconstruct the entire experience using my LinkedIn data export and emails.

And the results were quite interesting.

Let's start with the numbers

Between June and September 2026:

Yes, you read that correctly.

104 out of 112 hiring tracks had no conclusive outcome that I could find.

Before anyone starts calculating the industry's ghosting rate, an important clarification: this is missing data, not proof that 104 companies deliberately ghosted me.

Some applications may have been rejected in portals I never checked again. Some were still relatively recent when I accepted my offer. Others may technically remain open.

But from a candidate's perspective, the distinction isn't particularly comforting.

You submit your application. You receive an automated acknowledgment. And then you wait.

Sometimes indefinitely.

Apparently, my qualifications improved dramatically in 14 days

Here's my favorite story from the entire experience.

On September 24, a company rejected me for a Senior Software Engineer, AI position.

Fair enough. Rejections happen.

Then, on October 8, a recruiter from that same company contacted me on LinkedIn.

My profile apparently looked like a strong match for their Senior Software Engineer, AI position.

Same company. Same job title.

Fourteen days apart.

I hadn't changed my profile or suddenly acquired ten years of additional experience.

Apparently, my qualifications improved while I was sleeping.

To be fair, these could have been separate requisitions, or the hiring requirements may have changed. Recruiting and applicant tracking systems don't necessarily share the same information.

But that's precisely what makes the experience interesting.

The candidate sees one company. Behind the scenes, multiple disconnected processes may be making completely different decisions.

Everyone wants AI engineers. Nobody agrees on what that means.

Another interesting finding: 30 of my 106 applications were for positions with AI-related terminology in their titles.

That's roughly 28%.

Some examples:

• AI-Native Software Engineering Director
• Technical Lead, AI Native
• Principal AI Engineer
• AI Solution Architect
• Lead Agentic AI Consultant
• Forward Deployed Engineer

As someone who has spent considerable time experimenting with coding agents and building AI-assisted development workflows, I was genuinely interested in many of these positions.

But there's an interesting problem.

What exactly is an AI-native software engineer?

Someone who uses coding agents effectively?

Someone who develops products using LLMs?

Someone who builds AI infrastructure?

Or an experienced software engineer with "AI" added to their job title?

Depending on the company, apparently any combination of the above.

My impression is that a significant part of the industry knows it needs AI-related expertise but is still figuring out exactly what that means.

And interestingly, the position I eventually accepted didn't have AI anywhere in its title.

The assessments before the humans

Another recurring theme was the increasing number of assessments before any meaningful human interaction.

I encountered:

• Cognitive aptitude tests
• Reasoning assessments
• Personality questionnaires
• Technical coding assignments
• Third-party interview platforms

None of these is necessarily unreasonable.

But when you're applying to dozens of positions, the time commitment adds up quickly.

There's something slightly absurd about asking a senior engineer with two decades of experience to complete hours of standardized assessments before anyone has spent 15 minutes discussing their actual work.

I'm not arguing that experience should exempt someone from technical evaluation.

I'm arguing that the order and proportionality of those evaluations matter.

The application that worked took 85 days

One of the biggest lessons was that hiring timelines are wildly unpredictable.

On June 22, I applied for two different positions.

One company rejected me that same day.

The other application eventually became my accepted offer.

85 days later.

Meanwhile, September was absolute chaos.

After a relatively quiet summer, I suddenly had multiple interviews, assessments, technical discussions, and recruiter conversations happening almost simultaneously.

On September 15, I accepted an offer for a Principal Software Engineer position.

I also had several other active hiring processes to withdraw from.

And naturally, recruiters continued contacting me afterward.

Apparently, the most effective way to attract recruiters is to stop looking for a job.

What I'd do differently

Looking back, a few lessons stand out.

1. Track everything.

LinkedIn and email barely overlapped in my reconstructed data. Relying on either source alone would have missed a substantial part of the search.

2. Don't interpret silence as rejection.

Silence tells you almost nothing. Continue applying until you have an actual offer.

3. Keep multiple processes alive.

My successful application took nearly three months. Had I stopped applying while waiting, I'd have been making a pretty terrible bet.

4. Make your technical experience obvious.

I actually had a recruiter question whether I had recent hands-on .NET experience because my CV emphasized C++ and cloud architecture.

Fair criticism. A broad technical background isn't particularly useful if the relevant experience is buried.

5. Clarify remote and hybrid expectations early.

Discovering a three-day office requirement after several interview rounds is a waste of everyone's time.

6. Read beyond the job title.

Especially when AI is involved. The actual responsibilities matter considerably more than whether the position is called AI-Native, Agentic, Principal, Staff, or something equally fashionable.

So, is tech recruitment broken?

I don't think my experience proves that.

This is one senior engineer's job search in one part of Europe, over one summer. It's not a representative industry study.

And 106 applications across different technical domains certainly wasn't the most narrowly targeted search imaginable.

But I do think the experience illustrates several problems worth discussing:

• Poor communication between hiring systems and recruiters
• Little useful feedback for candidates
• Increasing assessment requirements
• Unpredictable recruitment timelines
• Confusing job titles, particularly around AI

The good news?

It eventually worked out. I accepted a Principal Software Engineer offer and started a new chapter in my career.

The slightly less encouraging news?

It took 106 applications to get there.

And I still have no idea whether some of those other 104 processes are technically waiting for me.

Perhaps I'll hear back in 2027.

I published the complete analysis, including the application timeline, detailed statistics, unusual recruiter interactions, and a few memes, on my personal blog:

106 Applications, One Offer: A Senior Engineer's Job Search in the Age of AI

I'm curious about other developers' experiences.

Is this what software engineering recruitment looks like in 2026, or did I just happen to play on hard mode?