Inside the Hiring Funnel: Truths and Tactics for API Pros Seeking Jobs

Net API Notes for 2024/04/17, Issue 236

Like last year, 2024 has seen its fair share of high-profile, tech-sector layoffs. Whether it is companies like Google, Amazon, and IBM reducing headcount or the increasing number of people utilizing the #GetFediHired hashtag within Fediverse posts, there are lots of API folks currently applying for jobs. 

I've spent much of my Q1 researching and talking about the macroeconomic drivers of the current API job market. From publishing technology and tool trends to breaking down how 'economic headwinds' reprioritize API program goals, from describing the shifting priority toward ROI to explaining how to adapt to industry shifts, things are, quantitatively speaking, weird

If you are currently seeking employment, you've undoubtedly spent time carefully updating a resume or CV. This might have included agonizing over whether your verbs are action-oriented enough, debating the proper amount of white space, and taking the time to tailor cover letters to each position's particularities. 

Unfortunately, all that effort may be a waste of time. In this edition of Net API Notes, I'll go under the hood to share my experience on how recruiting actually works in large enterprise organizations, discuss the implications of the last decade's "industrialized" HR process, and explain why that extra care and effort you're expending may be costing you callback opportunities

That, and more, in this Net API Notes. 

The Idea of Recruiters Dutifully Reviewing Candidates Is A Myth

Even after I had joined several Fortune 500 companies, I still believed that all applications for a job were carefully reviewed and vetted by humans deeply invested in the process. It was only later that, working with HR, I got a better understanding of the truth: "internet scale" has drastically reshaped how internal company recruiters perform their jobs. 

The ubiquity of online listings means company recruiters are constantly inundated with qualified candidates. Posting a position to a site like LinkedIn has the advantage of giving the company with an open position tremendous reach. LinkedIn also makes it trivially easy for candidates to apply; in many cases, employment history and education can be shared in a click or two. Other career sites have similar functionality.

The flip side of that wide distribution and ease of application is that now somebody within the company has to triage an internet's-worth of attention. As the anecdotal evidence from Reddit suggests, a software job posted to LinkedIn may have 200 applications within the first few hours

Reading resumes is not a recruiter's only job, either. In addition to (most likely) juggling the hiring duties for multiple positions, these recruiters also attend candidate prescreens, wrangling meetings with hiring teams, and following up to candidate questions in addition to processing hundreds of resumes per week. As a different Reddit post by a former Meta/Google recruiter points out, this means spending less than 30 seconds on any single resume

I want to underscore this point: recruiters are not operators standing by, looking forward to taking your call. Modern online recruiting has absolutely clogged the top of the hiring funnel for all but the most esoteric or high-level jobs. Coping often means cutting off candidates after the first couple hundred submissions, something that might happen within the first few hours of posting. No matter how meticulously tailored, every submission after that cutoff risks being ignored. 

"Also senior, applied to close to 300 jobs last 3 weeks. Most of my interviews are referrals, organic call back is at like 3%." - YetAnotherSegfault

If that sounds bleak, it is because it is. But wait, there's more!

Triaging Means Keywords Have Elevated Prominence

To try and manage this firehose of information, vendors have started promoting AI-conducted interviews, which… is all sorts of ick. (As someone who professionally performed at a high level but typically does poorly on these narrowly defined litmus tests, I am confident in saying that companies that follow this approach will reap the brittle monocultures that they sow.)

A screenshot of X (formerly Twitter) advertising an "AI Interviewer"

While most job applicants aren't being evaluated by dead-eyed simulacrums (yet), there is undoubtedly some pattern matching still happening. When I was a people manager, hiring would always start with a conversation with my assigned recruiter. We would talk about the position at length. This wasn't because I was such a pleasant conversationalist; the recruiter needed to understand how I spoke about the role, taking care to note the words I used so that they could apply those terms during resume evaluation.

Whether performed by a human or processed by an algorithm, resumes aren't read; they're scanned. If an application has enough "hits", it goes into the pile to be pursued. Does a term search result in a 404 not found? Unfortunately, the resume will likely go unseen; there's not enough time (or subject matter expertise) in these initial stages for in-depth analysis and too many other options for benefit-of-the-doubt. 

Consider the following examples:

While formatting and grammatical flourishes are wasted at this stage, the examples above show that submitters should ensure their resume reflects the language used in the job listing. Providing a resume as is and expecting an overloaded recruiter to connect the dots is unlikely to happen. If the job listing is looking for a 'Swagger designer', make sure your OAS experience mentions Swagger somewhere in response. 

How to Increase the Odds of Getting a Callback

Thus far, I've made the case that the speed at which you submit your credentials to a job listing matters far more than any formatting concerns. However, increasing your rate of getting a follow-up response requires a two-pronged approach: one to use immediately and the other to apply long term. 

The Short-Term: Using Generative AI To Identify Keyword Gaps Faster

If you're going to do any customization, ensuring your resume echoes the terminology and language mentioned in the job listing is priority . 

Next, if you have access to a tool like ChatGPT or CoPilot (Microsoft-adjacent), Gemini (Google), or Claude (Anthropic/Amazon), you can take this one step further. Once you've provided your resume and the possible job listing to the generative AI system, we can do some pattern matching. You may ask the LLM several clarifying questions, like:

  • What roles on the resume demonstrate relevant experience wanted by the job listing?
  • Which roles should be rewritten or re-worded to match the job listing better?
  • Which tools, techniques, or patterns required the listing requires are missing from the resume? 
  • What achievements or quantifiable outcomes on the resume speak directly to the job listing - things like improvements in performance, cost savings, or successful project completions? 
  • Which achievements or quantifiable outcomes don't relate or distract from what is desired by the job listing? 
  • Does the resume adequately mention the teamwork, leadership, problem-solving, and communication skills suggested by this position? 
  • Does the resume demonstrate continuous learning and professional development that is aligned with what a successful candidate for this job would have? 

The answers to those questions will provide insights into inherent strengths or potential gaps you may have become blind to. Ideally, you'd do this process with a trusted mentor or peer. However, given that speed is of the essence, generative AI provides a degree of helpful feedback in an on-demand manner. 

NOTE: I am NOT advocating that you keyword stuff your resume. Overloading your application with buzzwords in an attempt to manipulate undermines both your credibility and authenticity. What I encourage instead is a thoughtful alignment of how you describe who you are with the position that's available.

The Long-Term: Your Professional Network

While carefully crafting your keywords is a short-term strategy, the long-term approach is to skip the scanning altogether by being referred. And the way of getting referred is to build, and maintain, a strong professional network. 

Hopefully, you've done the work to keep track of people you've worked with. These may be inspiring leaders, enjoyable peers, or "partners in crime" (the benign, "us-against-the-bureaucracy" kind). If you haven't kept up with these folks, then immediately after finishing this piece, brainstorm at least six people you'd want to work with again. To your list of a half-dozen people, identify how you might contact them. Some might have a presence online, publishing to their blog or via social media. You might have the email for others. Finally, failing that, see if you're connected with them on LinkedIn and, if not, add them. 

Reestablishing those relationships doesn't require writing an abridged summary of your life since you last talked. Pinging these people can be as simple as sharing that it has been a while since you worked together (on a specific project) and you happened to be thinking about them. Then, ask what they've been up to and let the conversation flow naturally. Do you have those awkward 10-15 minutes between meetings in your workday? Those moments are perfect for these touch-base opportunities. 

When you've done that for your first half-dozen, repeat those steps for the next six that come to mind. Of course, if you live nearby, you can escalate this to grabbing coffee or catching up over lunch. The bottom line is that growing a professional network is a lot like planting a tree - the best time to do it was twenty years ago, and the second best time is now. 

Then, when it comes time to find a new job, your network can help you bypass the challenging initial step.

Keep Working It

I acknowledge that boiling years, sometimes decades, of rich, nuanced experience into a few keywords is belittling. Racing to be the first to respond to a new opportunity feels desperate. I get it. Just remember this is just an intermediate step in getting your foot in the door - it is not the totality of you or the process. After you get the callback, you'll have the opportunity to expand this handful of keywords into a more fully formed, fleshed-out picture of the real you.

I've been in your shoes more often than I'd care to remember. And while applying for jobs may have changed significantly since the first time I was laid off, during the dot-com bust, the advice I got then essentially still applies. With some awareness and a few tweaks, you can increase your callback rate and get back to making APIs.

A signed copy of Work It! by author Allison Hemming


Wrapping Up

Thanks for reading yet another issue! If you want to financially support Net API Notes, try the subscription page. A monthly or yearly pledge helps Net API Notes remain ad-free and ensures previous commentary, analysis, and insights remain available for all. 

That's all for now. Till next time,

Matthew (@matthew in the fediverse and on the web)

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