As tech companies shell out millions for top AI talent—even reportedly billions—regular rank-and-file employees are left wondering how to get in on the action and land a job in artificial intelligence.
One report found that job postings that mention needing at least one AI skill had salaries 28% higher than other jobs, which translates to $18,000 more. Jobs that required two AI skills had a 43% salary jump.
To begin with, it’s worth considering where the AI jobs are and how this intersects with your interests and existing skills. Many jobs in AI can roughly be divided into five different categories:
- researchers
- engineers
- business strategists
- domain experts
- policymakers
Researchers bring a deep understanding of neural networks and algorithm design to the table and can push the technology forward, but this is a very small pool and typically requires a PhD.
Engineers typically have programming skills that they can use to build AI applications.
Business strategists can fold AI into their company’s workflows and processes, or spearhead product development.
Domain experts understand how to apply AI to their field, while policymakers can craft AI ethics and use guidelines.
But what do you do once you’ve identified where you want to go?
Getting experience in AI, and developing skills in it, is a tricky proposition because the field is still so nascent. Plus, things are evolving at breakneck speed; what worked a couple years ago may not be a silver bullet today. But some strategies—being scrappy, curious, and adaptable—could prove timeless. We interviewed both HR and recruiting pros, as well as people who have managed to build up their AI skills to land a job in the industry, to learn:
- What AI industry insiders at LinkedIn and Amazon recommend are the surefire ways to get a hiring manager’s attention
- How workers are turning their regular jobs into “AI jobs” to get experience
- Where one talent recruiter looks to see if someone is working on developing AI skills
1. Figure out ways to learn on the job
While companies such as Boston Consulting Group (BCG) and Thomson Reuters are rolling out company-wide initiatives to ensure their entire staff gets trained in AI, that isn’t true of most companies. Only 2 in 5 employees report receiving AI training on the job.
If your company doesn’t have AI training, get on projects that do involve AI.
“Get some experience at your existing company before you try to jump into a truly AI-focused role,” says Cheryl Yuran, chief human resources officer at Absorb Software, an AI-powered learning platform provider. “Have something on your résumé to talk about from an AI standpoint.”
Yuran points out that Absorb isn’t able to find enough people with AI experience for all of their teams. That’s how few people are out there in the workforce with an actual background in it.
Instead, the company makes sure there are one or two members with AI experience on their teams. The remaining jobs go to candidates or insiders who demonstrate they can add value, whether it’s deep product knowledge or excellent communication skills.
If there aren’t AI projects or initiatives at your job, create them. Or experiment with ways to use AI to help you do your job.
Gabriel Harp, a former product manager for multiple companies in academic publishing, oversaw the launch of an AI-powered writing assistant in 2023 at Research Square, an Inc. 5000 company. “Although my degree is in English and German, I’ve spent more than a decade building software products,” Harp says.
For the AI writing assistant, Harp set the initial vision and scope of the project, working on the branding and go-to-market strategy, conducting quality analysis, and much more. Harp wasn’t an engineer, yet he still leveraged his background to get great AI experience just before it was popular (or needed) to have any.
Since then, he’s served as head of product strategy at a startup that uses AI to build privacy tools.
When Harp went on the job market, he had plenty to discuss during interviews, although he has a degree in the humanities. “Since I’d been using AI in the workplace, I was more familiar than the average person with these tools,” he says.
He recently landed a senior staff product manager job at Mozilla.
“We’re seeing a lot of emerging talent or people who want to shift their career path,” says Prashanthi Padmanabhan, VP of engineering at LinkedIn, who regularly hires for AI talent. “Nothing beats showing you’ve actually [used AI] on the job.”
2. Take a course
If getting close to an AI project at work isn’t an option, you can always take courses.
Right before the pandemic, Amanda Caswell was working as a copy lead at Amazon when she became interested in AI. She started listening to podcasts about AI and signed up for courses, including an online prompt engineering class at Arizona State University, an AI boot camp by OpenAI, and a generative AI and prompt engineering master class by LinkedIn.
“Start at the 101 level, even if you have some experience,” she says. “That way you’ll know industry best practices, which can help you teach others. Because who knows? You might have to do a job in AI training.”
In 2020, Caswell started getting gigs as a prompt engineer at Upwork and has made close to $200,000 on the platform, only working about 20 hours a week. In addition, her knowledge of prompt engineering helped her land a job as an AI journalist at Tom’s Guide.
Similarly, Cesar Sanchez, a full-stack engineer (who is now an AI engineer) became interested in AI in 2023. He immediately signed up for a Coursera course on generative AI with large language models to get an understanding of the fundamentals.
“It was a great decision. It offered me a strong foundation and helped me understand the theory,” Sanchez says. He also signed up for another course that offered him access to a network of AI engineers. “While I didn’t necessarily learn new things, I was able to connect with other engineers and compare my skills to what else was out there in the market,” he adds. “Plus, I got lots of free credits for using tools and platforms.”
3. Take on a side project
However, even if you aren’t able to fold AI into the job or take a course, recruiters say there’s always the trusty side project. Having a side gig is often a privilege that’s unavailable to some, but having one can sometimes grow into something that’s more full-time, sustainable, and meaningful, regardless of the field.
AI, experts say, may be no different.
“A lot of candidates will say, ‘I just focus full-time on my current role,’” says Taylor King, CEO of Foundation Talent, which recruits for top tech startups. “But the ones really thriving are the people who dive headfirst into new AI or LLM tools, constantly experimenting and building on the side,” he adds. “An active GitHub tells you they’re genuinely curious—someone who’s growing beyond the boundaries of their job, not defined by it.” (A McKinsey report found that people who are adaptable are 24% more likely to be employed.)
Nico Jochnick had no background in AI, but managed to land a job as lead engineer at Anara, an AI startup that helps research teams organize and write scientific papers. He says he got a job in AI because of his experience using AI for side projects.
“I was fascinated with AI and using Cursor to code side projects, and was doing hackathons,” he says. “[Anara’s founder] and I knew these tools were giving us tons of leverage, and we connected over that.”
While Harp, now at Mozilla, was job searching, he also worked on AI side projects, such as using AI coding tools to create a bingo game for his favorite podcast, as well as a recruiting tool in ChatGPT that allowed recruiters to ask questions about his work experience. “I was worried about getting rusty,” he says. “I needed to continue experimenting with the tools out there.”
4. Create your own job
Ben Christopher, a screenwriter, taught himself to code in order to keep the lights on. He started experimenting with AI in 2022 and built Speed Read AI, a tool that summarizes scripts and provides business insights, such as budget estimates, for Hollywood executives. “I started showing it to some people in the industry, and got enough feedback where people said, ‘We’ll pay for that,’” Christopher said.
Today, his team is five people strong with a growing customer base. (Christopher is careful to stress the point of Speed Read AI is to help Hollywood executives dig through massive slush piles and find more unique scripts.)
Meanwhile, Victoria Lee originally trained as a lawyer but then took a coding boot camp when she felt like she was getting pigeonholed in her career development. She graduated from the boot camp and got her first coding job in 2022, a few months before ChatGPT launched publicly. In her spare time, she had started putting publicly available legal contracts into ChatGPT for analysis and comparing them with her own. She built an understanding of what ChatGPT did well, and where it had gaps.
Lee realized the legal industry was embracing AI, and that she was perfectly positioned to fill a gap; she knew what lawyers wanted and also knew how to speak to engineers.
She landed a job in product strategy at eBrevia, which uses AI in mergers and acquisitions (M&A) due diligence. However, Lee realized she could add more value by creating her own company. Today, she provides legal services for, as well as works with, mid-market law firms to help them implement AI and craft AI policies.
Lee recommends that people who want to go into AI should “identify their specialty” and build “knowledge to understand how it can work better with AI, or where AI currently falls short.”
Jochnick has since left Anara to found his own AI-powered company, which is still in stealth mode. “The people I’d hire are already building projects and putting them out in the world,” he says. In fact, Jochnick notes the biggest mistake you can make today when experimenting with AI is not trying. “It’s insane to see how much more powerful you can become in a few months. This is a really fun journey to be on. Everyone should be upskilling themselves.”
