The AI Recruitment Episode: Why Tech Hiring is Getting Harder

937 applications. 42 interviews. 80 days. That's what it took one experienced data scientist to land a job in 2025—and he's one of the lucky ones.

In this episode of The Catalyst, we follow two tech professionals through what they call "the worst job market ever." Emily, a software developer with 10 years of experience and a degree from University of Waterloo's prestigious computer science program, gets laid off on a Tuesday and was interviewing the next day. Santiago, a data scientist and former manager at Deloitte, launches what he calls a "denial of service attack" on the job market—bombarding it with nearly a thousand applications while tracking every rejection in a dashboard styled like Super Mario.

Both land jobs. Both consider themselves fortunate. And both say the system is fundamentally broken.

Meanwhile, over 700 tech workers are being laid off every day while companies claim they can't find talent. Something doesn't add up. Through their stories and expert analysis from Bobby Burns, Vice President of R&D at Indeed, we uncover what's really happening: applicant tracking systems filtering out 75% of qualified candidates, AI conducting first-round interviews before humans ever get involved, and a catch-22 nobody can solve—where will senior developers come from in 2030 if we're not hiring junior developers in 2025?

Key Takeaways:

• Why the "talent shortage" exists alongside mass tech layoffs
• How applicant tracking systems reject 75% of resumes due to formatting issues
• The psychological toll of sending hundreds of applications into the void
• What AI tools might (and might not) fix about hiring and fighting bias
• Why even graduates from top programs can't get entry-level roles

Read about Emily's experience on her Medium: https://emilyxiong.medium.com/my-experience-of-finding-a-tech-job-in-2025-6830297c5197

---
---

This episode is brought to you by Softchoice, a World Wide Technology company. We work with mid-market IT leaders on their biggest challenges, including how to build and retain great teams in a market that makes it harder than ever. Visit softchoice.com to learn more.

Listen now at: softchoice.com/podcast

#TechJobs #Hiring #ITCareers #JobSearch #TechLayoffs #TheCatalyst #Softchoice

The Catalyst by Softchoice is the podcast dedicated to exploring the intersection of humans and technology.

Transcript

0:00

It's a Tuesday morning in August, 2025. Emily Chong is ready to work after a long weekend, but then her manager sends her a slack message asking if she has time for a quick call. At least it's not through a email. It's actually a video call. So I took a day off and, uh, actually I'm pretty fortunate that like next day I got interview and uh, I start to interview for a different company. 10 years in software development, a degree from University of Waterloo, one of the most prestigious computer science programs in Canada. Emily is laid off on a Tuesday and then interviewing for a job the next day. Emily would eventually land a new job within a month, which in 2025 counts as lucky. Except I do think this year is the worst job market I ever seen. This is the worst job market she's ever seen. Even after landing a new gig relatively quickly, because here's what Emily knows, she's the exception. This year I went to a lot of meetup, so this year I can sense from a meetup. In Toronto that the economy is not doing so well. I heard a lot of stories in media groups that people got laid off. In 2023 according to tracking site layoffs. Fyi, over 264,000 tech workers were laid off the worst year since the.com crash of 2001. In 2024, another 151,000, and in 2025, it's still going. About 700 tech workers a day are losing their jobs. Meanwhile, companies claim they can't find talent. Something isn't right here. From Softchoice, a Worldwide Technology Company. This is the Catalyst. Today, the new brutal normal of tech hiring. How the game is rigged, why even the winners say it's broken, and what it actually takes to survive. Act one, the gauntlet. Let me show you what it actually looks like to search for a job in 2025, not the LinkedIn post version where someone lands their dream role and thinks their network. The real version. Santiago is a data scientist. He had a manager title at Deloitte last October. He came back from parental leave to some news. So in 20 23, 20 24, I forget the exact date I had started at Deloitte. I was a, uh, manager, uh, on a data science team in Deloitte. Sometime around middle of the year, 2024, I went on parental leave. Deloitte has a generous parental leave policy. Santiago took the first half, came back for a bit, and planned to take the rest later in the year, except when he came back in October. It's October, 2024 and I, uh, am informed that my department has been laid off, and then two weeks later I am out of a job. So that's how I ended up being in the market unwillingly. And here's where Santiago's data science brain kicked in. Initially, of course, it's that, oh, craft moment, right? What am I gonna do? Start formulating a plan. I have a very young child, so I'm already awake really early in the morning, so my day starts somewhere between three and five in the morning, three to five in the morning. Baby's already awake and Santiago decided on a strategy. I'm going to sort of like a denial of service attack. I'm going to bombard the system with my application. I'm not gonna be picky. I'm not gonna be choosy hotkey. I'm pretty good with hotkeys. My whole focus is just apply to everything and anything regardless of job title level, just. I need to know how the market values me. A denial of service attack, that's a term from cybersecurity. When you overwhelm a system with so much traffic, it can't function. And because he's a data scientist, he built a dashboard to track it. I have a CSV file where I track all the applications. Nothing too crazy. It's just the data I applied, the title, whether it's uh, in office remote and a few other fields, a few other. Attributes about the jobs, and I build a dashboard to track this work. He made a dashboard like something out of Super Mario, because if you're going to document your unemployment, you might as well make it playable. The centerpiece is a graph styled like a Mario level. Each red brick represents applications sent that day. As the day stacks up the bricks climb higher and higher. Some days towering, some days dropping down 80 days. That's how long Santiago spent in the market stacking those bricks. And at the end of those 80 days, here's what the dashboard showed. 937 applications, 42 interviews, 28 rejections, 10 roles. He turned down himself. One, offer fur. And remember, Santiago is one of the success stories. So what's happening in that gap between sending a thousand applications and getting 42 interviews? The answer software specifically applicant tracking systems at s for short. According to research from Job Scan, 98.4% of Fortune 500 companies use these systems to screen resumes before a human ever sees them. And here's the problem. Studies show that 75% of resumes get rejected by a TS simply because of formatting issues. Emily, the software developer from Toronto has been watching this happen to people she knows. Recent graduates from top programs unable to get their foot in the door. Waloo students, uh, CS core program, that's the crown jewel of Canadian education because people out that program can make six figures. Right away out of school. But I heard stories for new grad from Waterloo. That is particularly hard because they don't have any experience and now very few companies are willing to hire junior developers. The crown jewel of Canadian Computer Science education, and even those graduates are struggling, which brings us to a brutal catch 22. I think for. Every job posting is probably getting hundreds of interviews. There's no way for HR person to actually review every, uh, resume one by one. Act two, the algorithm, hundreds, even thousands of applications for one role. Companies can't look at all of them, so they turn to software. To ai to algorithms, which is where Bobby Burns comes in. So I'm Bobby Burns. I'm the Vice President of r and d at Indeed. My team specializes in two things. One is growing the indeed flex marketplace for temporary workers, and then we're building, uh, SaaS, uh, software that we're providing to all indeed employers that we've kind of homegrown for ourselves, uh, to grow the flex marketplace. Indeed is the world's largest job site. Over 350 million people use it every month, and Bobby's team is building the future of hiring AI tools that are supposed to make everything better, more efficient, less biased, and more fair. We try to take the pool of job seekers at Indeed and the pool that of people that are applying for and try to perfectly match the people that you're looking for. And so one of those components may be we will reach out to them and do an AI recruiter and ask them specific questions. That way we can play back to the employer if, if this job seeker or not kind of matches what you're looking for. Our producer asked Bobby about what he sees in the market right now. Whether it's as bad as people say, it's so from what I've seen, I do believe that the tech industry is being impacted quite a bit, and for somebody that is kind of especially new to their career or new to being a developer, it's extremely challenging. More and more jobs seem to be offered to more senior roles if the role is available. A really challenging time for both sides. Companies can't find the talent they need. Job seekers can't get past the algorithms and sitting in the middle of all of this recruiters. Here's something we don't talk about enough. Recruiters are drowning too. When a single data scientist role gets a thousand applications, someone has to process that. Someone has to figure out which 3% make it past the first screen. Someone has to schedule interviews, send rejections, keep the pipeline moving. That's why AI tools exist in the first place, not to be cruel, to manage the impossible scale. Even prior to the chat GPT era, job seekers weren't getting employers to reach out to them and realize that it, it becomes a numbers game. So they just started applying to all jobs. They didn't read necessarily exactly what they were looking for for them, they just applied. Then when you sprinkle on these LLM and AI tools that can automatically do it on your behalf, it is a huge order of magnitude higher. That is why I think you're starting to see AI interview tools and AI recruiting tools emerge on market because employers are just drowning. So they need tools to help you add the tools to help, uh, and that gets into situations where it takes away the human being. AI is there to surface the best candidates, make the impossible, manageable, give recruiters a fighting chance to actually do their jobs. Well, that's the theory anyway, but here's what it actually feels like when you're on the other side. So I did a couple interview where the first round of interview is not, I am calling an HR for a quick chat. It's basically a semi, a series of tests that is conducted by ai. The AI asked me some like very technical, but also some behavioral question and they just evaluate me right away. And by the end of like the first round of interview, I can see the AI output and it's telling me whether I'm qualified or not. An AI telling you whether you're qualified before you've ever spoken to a human. That is very strange for a person who like never met a company, never met anyone, but just going through an interview with AI for interview. It goes both way. I'm evaluating the company as well, so if a company is first run. It's conducted fully by ai. So what does that say about the company as well? What does that say about the company? It's a fair question, but Bobby says, many of the AI tools built for recruiters are actually about making things better, more humane. He talks about AI being used to filter out bias. When they're reviewing the AI interview, the AI is able to kind of say, based on what I've heard here is how I'm ranking them for, uh, certain skill sets, et cetera. But still let the human in the loop make, make the decision there that will remove the bias more and more than what you previously would've done with human to human. I don't think we ever had an effective way of measuring bias with human to human interviews. I think it changes the conversation when a unbiased LLM is providing here is what I heard from the scores, and if you're going to override me, that's fine, but you actually have to justify why they're being overwritten. Okay. We need to pause here for a second to talk about bias in AI recruiting because when you look at the research, it starts to get. Messy AI recruitment tools have been shown to discriminate against women and people of color because it's trained on historical data that just amplifies existing biases. Here's an example. When AI learns from companies that historically hired more men for tech roles, it starts prioritizing keywords like technical leadership. Or project management terms that tend to show up more often in male candidates resumes, qualified women with the same skills, a different wording get ranked lower. The algorithm isn't being neutral, it's learning to repeat the past. Bobby himself acknowledges things aren't perfect yet and that there's a lot more work to do. I, I think it'll continue to evolve more and more. We're trying to get humans that know what good looks like, but leverage AI in a way to parse that for thousands of job seekers. Now, act three the way forward. So what do you actually do if you're Santiago sending a thousand applications? If you're Emily watching the world's smartest grad struggle to get entry level jobs, if you're a recruiter drowning in hundreds of applications for a single role. What's the move today? Right now? So my thought with the job seekers is use the time to actually refine or create new skill sets for you. And the reason I say that is because I think what could set you apart from other job seekers that are going through the exact same things that you are, is you'll be able to tell a story about what you've learned, challenges that you faced, and how you evolved from that. Learn something, build something, have a story to tell that's not just, I applied to 500 jobs and got ghosted in this new platform that we're moving to towards with LLMs and AI tools. That's gonna be necessary and people are going to want to see that you're gonna be able to ride the wave, so to speak. Bobby also has something to say to the other side of the table, the recruiters. The hiring managers. And then the second I think for recruiters is go into this knowing that every candidate you meet, this is not the first or second time they've interviewed somebody. This is the 10th time, this is the hundred time, this is maybe the thousandth time. Every person sitting across from you has been through this gauntlet dozens or hundreds of times already. Ask some of those probing questions. Take a leap a little bit on the person that doesn't necessarily have a hundred percent of the skills that you're looking for, but is able to evolve and is being able to demonstrate that they're able to evolve. In other words, sometimes the right move is take a leap on someone who doesn't check every box. Santiago has his own take on strategy. He tried the denial of service attack approach, a thousand applications in 90 days. It worked for him, but he knows it's not the only way different approaches work, right? So you have the, what I call the denial of application attack, bombarded the system that works. The other alternative. Is a very strategic surgical approach. My colleagues also found jobs doing that approach and times different, different approaches work. There's no one right way santiago's. Thousand applications worked for him. Someone else's careful, targeted approach works for them. The only common thread, whether it's three months, six months, or a year, if you keep at it, you keep honing your skills, you keep practicing eventually. You'll find and land that role eventually if you keep at it. If you don't give up, if you can afford to wait six months or a year, you'll find something that's the survivor's advice, but it leaves one question unanswered. The thing Emily identified right at the beginning, the catch 22, that nobody seems to have a solution for. Waloo students. That's the crown jewel of Canadian education because people out that program can make six figures right away outta school. But I heard stories for new grad from Waterloo. That is particularly hard because they don't have any experience, and now very few companies are willing to hire junior developers. They're getting the best education possible, and even those graduates can't get their foot in the door. Where do the senior developers of 2030 come from if we're not hiring junior developers in 2025? Nobody has the answer to that one. Emily doesn't have the answer. I don't know the solution to that, but I just think companies just should invest in junior developers on carbon new growth because like in 10 years from now, where's all the senior developers going to be? Don't start. Bobby doesn't have the answer either. I can't forecast this one. I can't say how we're going to react to. Fewer and fewer jobs to get that experience necessary to become that senior. Nobody has the answer, not the people building the AI tools, not the people who survived the gauntlet, not the companies claiming they can't find talent while their algorithms filter out. 97% of applications. Emily found her job relatively quickly. By 2025 standards, Santiago sent a thousand applications and came out on the other side with a better role. Bobby's building tools to fix the system. They're all success stories and even they know it's broken. The new brutal norm. A place where even winning feels like losing. Where survival requires denial of service attacks or mastering the art of interviewing with a robot. The advice, keep trying. Eventually someone will say yes if you can wait that long. At Softchoice, we work with Mid-Market IT leaders on their biggest challenges, including how to build and retain great teams in a market that makes it harder than ever. If you are navigating these hiring challenges or if you're in the job, search trenches yourself. Share this episode. Let someone know they're not alone. Emily wrote about her job search experience on medium. You can find her story@emilychong.medium.com. It's worth the read. The Catalyst was reported and produced by Tobin Rimple and the team at Pilgrim Content Editing by Ryan Clark. With support from Philippe Demas, Joseph Beyer, and the marketing team at Softchoice. Special thanks to Emily Chong, Santiago and Bobby Burns for sharing their stories and insights. I'm Heather Hash. Skin. This is the Catalyst by Softchoice, a worldwide technology company. Thanks for listening.