Best First Jobs in AI That Will Keep You Competitive

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It’s inescapable — artificial intelligence (AI) now impacts you every day. You see AI at work when you interact with an online chatbot, scroll through your social media feed or ask your phone’s voice assistant a question.

This massive technological shift not only changes how you get things done in your personal life but also presents a world of new professional opportunities — and new ways to make money. As AI gets increasingly ingrained into society, businesses will need more highly trained experts to meet the demand.

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But how do you break into the AI field? Several entrepreneurs and business leaders chimed in, offering their insights into the best first jobs in AI and how to learn the skills you need to stand out amongst your peers.

Best First Jobs in AI

Here are four of the best first jobs in AI.

AI Intern

Nathan Brunner, CEO of boterview (an AI interview preparation bot), said the best way for bachelor’s and master’s degree holders to launch their AI careers is to land a machine learning or data science internship — ideally at a big tech company.

“These big tech companies have some of the best AI talent in the world, meaning interns learn from top-tier researchers. You will also have the opportunity to work on massive datasets and real-world scalability challenges,” Brunner said.

Prompt Engineer

Prompt engineers strive to create ever-improving prompts to get the best possible output from an AI system. “Prompt engineering could be a great introduction if you have zero experience because you learn through direct interaction with large language models (LLMs) and gain a deeper understanding of their capabilities. If you want to work in AI content creation, for example, that’s often enough to get started,” said Jacob Barnes, co-founder of FlowSavvy, an automatic time-blocking to-do list app.

“It’s not a traditional ‘technical’ AI role,” Barnes added, “but it exposes you to practical applications of AI and can be an important stepping stone to more specialized roles. When you learn how models ‘think,’ you become a great asset to companies looking to adopt these technologies — and that’s practically everyone right now.”

Data Analyst

“[Data analyst] jobs allow you to work with datasets, perform exploratory data analysis and sometimes even deploy simple models,” Brunner said. You might also see the position listed as a business intelligence analyst.

“Machine learning (ML) is a great progression of data analytics, so once you get started, if you like it and are dedicated, you will get into ML in no time,” said Ximena Gates, founder of BuildWithin, an AI workforce development company. “While data analytics is more about exploring, visualizing and communicating insights, machine learning is about building, training and testing predictive models.”

Software Developer

“Being a developer these days is way easier because you don’t need to have lots of programming experience. Being ‘entry-level’ can be as simple as knowing the fundamentals of JavaScript, React and some Python and leveraging AI editors like Cursor for speed. [You also need to] have problem-solving [skills] and attention to detail,” Gates said.

Gates underscored the competitive nature of this role — and the immense opportunities for top talent. “We’re heading toward a future where we’ll need fewer but more complete engineers, people who can code, deploy and even design while knowing when to leverage AI tools to optimize the entire development cycle,” she explained. “In the past, you might have specialized in one area, but now AI tools help developers become broader contributors, making them more valuable and giving them greater upward mobility.”

Boris Lapouga, co-founder and CTO of Primetime.so, an AI-based co-worker, followed this career path. He started as a software engineer more than 16 years ago but became interested in AI with the introduction of ChatGPT. Through self-study and practice, he ultimately built and sold AI agents and launched an AI startup, which recently received funding.

Best Ways to Learn AI

You should do three things to learn AI: study, practice and network with other professionals.

Education

Brunner noted that you’ll generally need a bachelor’s degree in math, statistics or computer science to get started in the field. However, he also encouraged learners to check out OpenCourseWare (OCW) from the Massachusetts Institute of Technology (MIT). “AI 101 offers an introduction to fundamental AI concepts and topics such as machine vision, data wrangling and reinforcement learning,” Brunner said.

Rennie Haylock, founder and CEO of Huntr.co, an AI-powered resume builder and job search management platform, encouraged interested parties to read widely about AI. “Blog posts, research summaries and podcasts often discuss new techniques long before textbooks are updated,” he said.

Haylock relies on these sources to stay current:

Hacker News
Y-Combinator’s Lightcone Podcast
the Every.to newsletter
ProductHunt

You can also learn a lot from content published by the foundational model companies, such as Anthropic and OpenAI.

Haylock offered this bit of wisdom to remember as you study. “Don’t get lost in the hype. Trends come and go, but a solid understanding of logical thinking and fundamentals never goes out of style. Focus on building that foundation and keep learning as the field shifts,” he said.

Experience

Knowing the theory behind AI is essential, but being able to put that theory into practice is even more critical. “If possible, jump into a real project early on — contribute to open-source AI tools or create a personal project with a friend. Hands-on experimentation sets you apart in interviews,” Haylock said.

“These days,” Haylock added, “anyone can build AI projects with minimal resources, so not having one can be a red flag. In fact, Huntr started as a personal project that came out of a hackathon.”

Gates agreed on this sentiment. “To stay competitive, keep up with all the new AI releases, experiment with the latest tools every day and compare what they can do,” she said. “At the end of the day (and I see this with our own engineers), the best AI makers are always the ones who actually use AI themselves.”

Networking

Working with others can fast-track your success. “You want to surround yourself with people who have a passion for the industry and are taking an active role in its evolution. Even when you start with no knowledge, you’ll learn quickly by spending 30 minutes a day reading and interacting with the right people,” Barnes said.

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