In this tough job market, rejections are commonplace. Part of the reason for frequent rejections is that the job requirements and the candidates’ qualifications do not exactly match, especially if they do not have AI/ML experience on their résumé or in their background. This can pop up only during some aspect of an interview, despite its absence in the job description. A competing candidate, more conversant with some aspect of their AI/ML story, can more easily breeze through that interview, despite a lower level of skill in the core area of the job.
Suddenly realizing that the job you are after springs a new requirement during your interview cycle can be destabilizing. Once an interviewer starts asking about your AI/ML skill that directly connects to the open job you realize that you’re toast. Unfortunately, you do not have any to showcase on the spot, which creates a “catch-22” dilemma: you dot have the experience because you have not worked in it and to get that experience you need that job!
In this blog I’m offering three strategies to make yourself more impervious to the vicissitudes of this job market, especially for those in high-tech verticals.
Strategy #1: The approach involves taking an objective view of the rejection and revisiting each step of the interview process to see if there are repeat patterns throughout different interview rounds and codifying these to build new interview muscle to prevent future such failures. For example, if you show a pattern of weakness in your leadership and behavioral responses then you know the area to focus on and building some strength in how your responses come across. Here, working with someone knowledgeable in these area and conducting a mock interview can help. Additionally, writing down your responses to typical questions in these areas can help you fortify your ability to ace future such encounters.
Strategy #2: You may even be one of the most qualified candidates in the core area of the job, but absent an emergent technology—AI/ML or any such development—aspect, you’re discounted. The best approach in this market, then, is to modify the previous job title in a way, that allows you to run a broader campaign across different job openings in adjacent areas and then getting in front of hiring managers to get yourself qualified for the job that fits their needs. This strategy does not obviate your need to showcase the missing skills, but it can provide you with new opportunities where such skills may not vitiate your candidacy.
For example, if your most recent title is SRE Lead—as it recently happened to one of my clients—and you are running against a brick wall in getting through the SRE interview rounds because you do not bring some AI/ML experience to the job, you’re not going to break through. So, changing that most recent job heading on your résumé to something with a broader market appeal can open more opportunities for you.
As you know, SRE is an infrastructure support role. So, titles such as Lead Infrastructure Engineer, Software Support Lead, or DevOps Lead may be able to help you if such job titles give you a broader reach to the current job market. This does not suggest that you are insulating yourself from being questioned on your AI/ML expertise, even in any of these expanded areas, but you are increasing your odds of being a qualified candidate if you otherwise are able to ace your interviews for these jobs. Here, you are increasing your odds for getting calls for interviews in the adjacent areas of your most recent job. Even with this strategy you can continue to pursue SRE opportunities as before.
Concurrently, signing up for relevant MOOC courses and getting conversant with some knowledge around the AI/ML areas that connect to your areas of interest, including SRE and seeing if that lifts your résumé and interview abilities can be a step in the right direction. Normally, getting a course certificate helps even more if you have some hands-on expertise beyond just acing that course, for which you can work on your own and in a group learning session. See if you can join some LinkedIn’s working AI/ML groups or form your own group of practicing AI/ML wannabes.
Strategy #3: The other approach to breaking through this impregnable job market is to also consider the prospecting approach to job search. This is where you have targeted a specific group of companies that you want to target and then researching each one to find their pain points that you can address with a cogent solution presented through a compelling prospect letter. These companies do not have a posted job opening for you to respond to. But through prospecting you are creating a job for yourself that only you can claim.
For example, if you want to target mid-size retailers that specialize in sportswear and fitness gear then making a list of such retailers and selectively prioritizing the top prospects can be a good start. Researching each of these targets and finding their pain points can help you frame a letter, offering a cogent solution to their needs and sending such a letter with your bio (NOT your résumé) by US Mail or overnight courier to the right decision-maker can open new doors. My own experience with such prospect letters—done well—shows a high success rate: about 25-30% of your submissions can go to the next step, opening some discussion on your proposed idea. Many of my clients have landed a job that they created through such strategies.
Yes, the current job market is hard to penetrate, especially for those in the high-tech space. Using these strategies can give you some additional opportunities that otherwise would be unavailable, so they are worth some effort. It’s hard work, but the rewards make it worth the effort!
Good luck!
