As artificial intelligence transforms the tech landscape, traditional "code-first" thinking is quickly dying. While AI can churn out functional code and solve complex technical problems, it lacks the human nuance required to build, manage, and scale real-world solutions that drive actual revenue; something AI is still poor at. But what separates the engineers who thrive in this new era from those who get left behind? Industry leaders from ONLC, The SaaS Jobs, and Praxica.io weigh in on the essential soft skills all technologists need to master, from strategic problem framing to AI oversight. These skills are quickly becoming the true currency for tech professionals who want to remain irreplaceable while the machine minds continue to gobble up the hard work of writing code.
What 4-5 soft skills make a candidate irreplaceable by AI?
Mitchell Ruebush, Chief Technology Officer and Head of Product at ONLC, gives us his soft-skills wishlist when vetting candidates:
- Networking - getting the right mentors, advice and help from other people is even more important with the fast changing world of AI - also can help soften the impact if AI causes loss of job.
- Juggling a bunch of different tasks as AI “workers” are doing the detail work, you can end up managing 40 AI workers and coming up with systems that can track and validate the work products is important.
- Envisioning what is actually important. AI can do create about anything and everything. But that will cost money in tokens and time in attention, which is the real limitations now. How do they break down problems into what is important and must have vs nice to have. How would they structure a project or application build so they get to the simplest deliverable quickly that can be used by the customer as soon as possible?
- Setting up systems to make sure quality and accuracy are in place. One thought is that these are skills that successful operations managers or audit/compliance would have in companies as they would manage lots of employees geared towards, how do I make sure that the person is doing the right thing when I can’t necessarily check everything that is going on because of volume.
- Curiosity, the simple question of what would AI do with this problem? How can I make AI do this better? How can I help the AI be self-sufficient in determining if it solved the problem.
Will Steward, CEO & Co-founder, The SaaS Jobs, adds, “you need to possess a skillset that allows you to shape the work you're doing before any AI even touches it. Problem framing is the most fundamental here because it determines what's being built in the first place. It's the ability to take an unclear situation, understand the real user need behind it, define the constraints, and decide what “good” actually means. Without this, even very strong execution can produce something correct but irrelevant. Judgment and critical thinking are just as important because AI systems can generate outputs that sound confident but are incomplete, misleading, or unsafe. The skill is not just recognizing when something looks wrong, but actively questioning assumptions and deciding when a solution should be refined or not used at all.”
How can a candidate demonstrate soft skills during the hiring process?
“I would lean into ‘Case Study’ style problems and questions which have a problem that they need to solve and the interviewer facilitates,” notes Mitch Ruebush, Head of Technology and Product at ONLC Training. “It is purposely a little vague in the initial description, but they can ask questions and show their logic and thought processes around this. Properly developed cases will look how they order the work and what is most important, curiosity in how they ask questions and approach the problem and structured right could show how well they establish the governance and checks and balances needed to manage a team of AI workers.”
“The strongest signal is how someone deals with unclear problems,” says Steward. “Good candidates start by asking what the goal is, who it is for, what constraints exist, and how success will be measured. They then talk through options instead of jumping straight to an answer, showing how they weigh trade-offs and risks. Explaining thinking step by step is often more important than landing a perfect solution because it shows judgment and structure. A strong close is a short summary of the decision, the reasoning, and what would happen next, since that mirrors real work.
“In take-home tasks, soft skills show up in how the work is explained. Being clear about where AI tools were used and how outputs were checked also signals responsibility. Including a simple way of testing or validating the work shows that quality matters, not just delivery.”
“The ability to make a call on when not to use AI,” is also important, adds Roland Jakob, Founder, Praxica.io. “Anyone can feed a problem into a model. Being able to determine whether the results are incorrect, whether using the shortcut will create long-term debt, and knowing when to stop and take a human decision, that is the gap we care about. I see this continually when reviewing work by contractors and junior builders. Those who stand out do not get things done faster using the tools. They understand when to rely upon them.”
How has AI changed communication requirements for tech pros?
“You are no longer buried in the code and just communicating with the machine,” Ruebush adds. “That is really the AI, so you need to communicate with the AI well to get the most out of it and you are acting as a manager now essentially (particularly as teams get smaller with AI taking on the roles of engineers (I am hearing and seeing the typical team of 8 going to 3 for delivering software in the age of AI). So those manager skills of communicating up and managing expectations and what is realistic with AI and timelines become more important. This is going to make a lot of tech pros sad because many found solace in communicating with machines through code in a deterministic relationship. AI has made this more probabilistic, like dealing with humans and many tech pros are revolting against this as this is not the world they are comfortable with.”
What aspects of resumes and cover letters show that candidates have great soft skills?
Ruebush tells Dice “It is hard to say with resumes and cover letters. Many of these are actually written by resume coaches that have good soft skills. If it is not well written, then that is a big red flag as they don’t know how to get advice and feedback or are unwilling to take it. The key accomplishments that highlight how they solved a problem through organization and teamwork is important highlights.”
Conclusion
Ultimately, the rise of AI does not signal the end of the technologist, but rather a shift in their core duties and primary focus areas. While the machine may now handle the heavy lifting of technical execution, uniquely human elements - judgment, strategy, and nuanced communication - provide necessary direction and oversight. By leaning into these soft skills and embracing the role of an AI-augmented strategist rather than a coder, tech pros can ensure they remain compelling in an increasingly automated world.
