Random thoughts on Engineering Hiring Strategies during Generative AI Proliferation
Today’s passing thought:
Many software engineering jobs are moving back closer to company headquarters, which is shrinking their talent pool options geographically again. From what I’ve seen job hunting over the past several months, this shift is real. Positions that used to be remote are increasingly listed as in-office or hybrid only. Many of the remote positions I see are ones that are continuously reposted. More than 50% of the positions I saw when I started my search are still up and being reposted weekly or monthly.
At the same time, there’s another trend pulling in a different direction: AI adoption is creating a divide within engineering teams. Whether it’s for coding assistance or business applications, organizations and engineers are split into two camps. Some are fully embracing the technology and see it as the future, while others are skeptical about its value and resist the change entirely.
As someone who’s all-in on AI and has been talking with engineering leaders during interviews, I can tell you there’s no consensus on strategy. One of my primary questions during interviews has been to ask about a company’s general AI position and or strategy. The responses I get are all over the map. Some say “if you’re interested in AI, this is probably not the position for you” while others want “AI forward engineers with 2 years experience building LLM backed applications.”
There is a big gap between those two positions that in my mind are clinging to traditional software engineering hiring strategies. From my perspective, to not have an active AI strategy is not good nor is saying “we only want people with experience with these specific tools”.
Generative AI, whether for coding or delivering business value through automation or novel products, is not about code or tools. It is about learning quickly and focusing on application of this new-ish technology in ways that deliver measurable business value. Both coding and AI applications require a different mindset and the time to experiment. “We don’t use AI” and “we want people who already have experience” both miss what I am speculating is the right balance for a digital strategy that will have legs over the next few years.
My point here, if there is one, is that I do not envy the position that the hiring managers are in right now. A list of must-know technologies and desire for engineers who want to work outside of their lane via AI empowerment makes for a near impossible candidate technical evaluation process :)
Strange days for sure...