Stanford professor turned AI startup cofounder shares insider tips to land a tech job fast: 'The playbook for AI is being written right now'

The AI job market may seem dominated by elite degrees and big tech résumés, but according to Jure Leskovec, a Stanford computer science professor and cofounder of Kumo, that’s not what actually gets people hired.

“If you want to work in AI, you need to show that you can actually do the work,” Leskovec told Business Insider in a recent interview. His advice is refreshingly straightforward: build real projects, work with public datasets, post your work online, and deploy demos.

Leskovec says hackathons are often where future AI stars shine. “They’re a fantastic way to demonstrate initiative and teamwork in a short time. Even if you fail, you’re showing that you’re curious and proactive,” he explains. One recent hire at Kumo caught attention because they built a generative AI tool to analyze customer purchase data — not because of a fancy degree, but because they showed real problem-solving skills.

Curiosity Over Credentials
For Leskovec, adaptability matters more than static skill sets. “AI is evolving at a pace that surprises even those of us who work in the field every day,” he says.

The best candidates are those who teach themselves new frameworks like PyTorch, JAX, or LLM tooling, and who stay on top of emerging areas like multimodal models, diffusion techniques, and reinforcement learning. Top schools might get someone an interview, he admits, but what gets them hired is curiosity, flexibility, and initiative.

“There’s no playbook for AI. We’re writing it right now,” Leskovec says. “I always value it when my students bring me solutions that haven’t been tried before, even if they’re wrong.”

Thinking Matters More Than Textbook Answers
At Kumo, Leskovec’s team evaluates applicants through multiple interviews that focus on how candidates think, not just what they know. Their problem-solving process often weighs as much as their final answers.

“It may sound simple to say, ‘think outside the box,’ but it is more critical now than ever,” he notes. He encourages aspiring AI professionals to question assumptions, try unfamiliar methods, and brainstorm multiple solutions to a single challenge. These habits, he says, are what set apart builders from followers.

Don’t Forget the Human Element
AI may be driven by algorithms, but hiring decisions aren’t. Leskovec says technical brilliance alone won’t get someone through the door. “I look for people who can communicate clearly, work well in teams, and think carefully about the ethical and social implications of what they’re building,” he explains.

Collaboration, empathy, and awareness of bias are just as important as coding skills in the modern AI landscape. “Your idea today could become the standard tomorrow,” he adds, “but it has to be built with people in mind.”

Jure Leskovec is a leading Slovenian-American computer scientist and a pioneer in large-scale network analysis and graph machine learning. At Stanford, he teaches one of the most popular machine learning courses and has co-founded multiple companies, including Kumo, which uses graph-based AI for enterprise data.