I didn’t realize it at the time, but being laid off from Meta became the launchpad for my transition into a cutting-edge career in AI prompt engineering. Many ask how I pivoted into this emerging field when few, including myself, even knew what prompt engineering was. The role is still evolving as companies create positions and integrate these skills, and every origin story is unique. Here’s how I shifted from TV news at CNN and NBC, and later news and strategic partnerships at Meta, to establish myself in prompt engineering. First, I identified the right opportunity. After my layoff, I was determined to stay in tech and researched where my journalism and tech partnerships experience could be valuable. I devoured tech news, analyzed companies, and job descriptions with a focus on stability and growth—especially companies likely to withstand or quickly recover from layoffs. During this, OpenAI’s ChatGPT frequently came up, signaling major industry changes ahead. As a former journalist, I was cautious about AI’s growing content role but recognized the emerging market opportunity. Next, I took calculated risks. I secured a contract role at LinkedIn’s news team—a company I admired—although it was a short-term, less senior position. Importantly, the job involved editing content for the platform’s new generative AI projects, which I saw as a valuable chance to gain relevant exposure. Even if the contract wasn’t extended, this experience would strengthen future applications. I also made a point to be curious and helpful. Before starting, I inquired about generative AI content quality work, which introduced me to the term “prompt engineer. ” While rating AI outputs, I provided clear, thematic feedback aimed at addressing broader prompt and training issues, hoping to deepen my involvement.

This approach paid off. Now, I focus on creating scalable prompts that minimize errors across multiple iterations, rather than writing one-off prompts for single tasks. I advise those interested in prompt engineering to look for ways to start within their current roles—offering help on AI projects or applying skills to annotate model responses—to prove their value and open doors. To further enhance my credentials, I added practical skills to my resume. Passionate about prompting, I noticed many job descriptions required some coding knowledge, especially Python. Although I didn’t write scripts myself, I interacted with existing ones and wanted to understand how they worked and how to troubleshoot errors independently. To do this and strengthen my candidacy without returning to school full-time, I completed an online Python basics course. This helped me communicate better with engineers, demonstrated commitment to my team, and gave me an edge in interviews, helping me pass coding tests and secure my current role as Prompt Director at an AI startup. Reflecting, the key lesson—whether in prompt engineering or any field—is to keep learning and remain open to new opportunities. Kelly Daniel is an AI prompt engineering leader with extensive enterprise AI experience. As Prompt Director at Lazarus AI, she develops prompt techniques and applications for large language models and cutting-edge tech like agentic models. She also instructs CNBC’s online course, How to Use AI to Be More Successful at Work. If you want a higher-paying, more flexible, or fulfilling career, try CNBC’s new online course How to Change Careers and Be Happier at Work. Expert instructors will teach you networking, resume revamping, and confident career transitions. Start now and save 30% with coupon EARLYBIRD on the $67 fee (plus taxes and fees) through May 13, 2025.