As artificial intelligence continues to reshape the professional landscape, tech workers at various career stages are sharing their proven strategies for landing cutting-edge AI jobs. The most consistent advice from successful AI professionals? Gain hands-on, real-world experience with AI technology rather than relying solely on academic learning.
Patrick Leung, an ex-Googler who joined the company in 2007, transitioned into AI when he joined the Google Duplex team in 2017. Despite limited prior experience building AI models, Leung retooled himself on the job by leveraging colleagues’ expertise. He now emphasizes that the barrier to entering AI is lower than ever, encouraging professionals to apply large language models (LLMs) to real business problems. He cites an example of a friend with no coding experience who used AI to personalize recruitment outreach messages, significantly improving response rates.
Sophia Sun exemplified this hands-on approach when she pitched an AI project at Kajabi, the creator commerce platform where she worked as a senior product manager. Starting in April 2023, she developed a tool using AI to help content creators generate marketing content for platforms like TikTok and Instagram. The project launched in March 2024, and by July 2024, Sun had landed a senior AI product manager role at Microsoft. She attributes her success to demonstrating end-to-end AI product development experience, emphasizing that building tangible products matters more than grades alone.
Mostofa Adib Shakib, a former Snap Inc. and ZipRecruiter engineer, recognized AI’s transformative potential when ChatGPT launched in 2022. He invested time learning from books, videos, and research papers while building practical projects, including a tool to help Bangladeshi professionals optimize résumés using agentic AI. In February 2025, Shakib secured an AI contractor role with Mercor, earning an impressive $6,400 per week. He chose contracting over full-time employment to maximize his time developing AI skills before the market becomes saturated.
Devi Parikh, former senior director of GenAI at Meta and current co-CEO of AI company Yutori, challenges the assumption that a Ph.D. is necessary for AI careers. Despite her own computer vision Ph.D. from 2009, Parikh prioritizes practical experience like model training when hiring. She recommends starting personal projects, engaging with open-source code, and building visibility through initiatives like her “Humans of AI” YouTube series, which she launched during the COVID-19 pandemic.
Key Quotes
People who can demonstrate they can wield LLMs effectively are going to find jobs.
Patrick Leung, ex-Googler and former Google Duplex team member, emphasizes that practical ability to use large language models is becoming the key differentiator in AI hiring, more important than traditional credentials.
Having good grades is one thing, but building a product that demonstrates your abilities is another.
Sophia Sun, senior AI product manager at Microsoft, explains why her end-to-end experience building an AI product at Kajabi was instrumental in landing her Microsoft role, highlighting the value of tangible proof of work.
I thought focusing on building AI skills before the market gets crowded was the right bet for me.
Mostofa Adib Shakib, former Snap Inc. engineer now earning $6,400 weekly as an AI contractor, explains his strategic decision to prioritize AI skill development through contracting rather than traditional full-time employment.
Not to assume you need a Ph.D. to break into AI.
Devi Parikh, former senior director of GenAI at Meta and current AI company co-CEO, challenges conventional wisdom about AI career requirements, noting she prioritizes practical experience over advanced degrees when hiring.
Our Take
This article reveals a critical inflection point in AI career development: the shift from credentials to capabilities. The convergence of testimony from professionals at Google, Microsoft, Meta, and successful AI contractors creates a compelling narrative that practical experience trumps formal education in today’s AI job market.
What’s particularly noteworthy is the accessibility message—that individuals can break into lucrative AI roles through self-directed projects and workplace initiatives, without expensive degrees or specialized training. The $6,400 weekly contractor rate demonstrates the market’s willingness to pay premium prices for demonstrated AI competency.
However, there’s an underlying urgency in these testimonials: the window of opportunity may be closing as the market becomes “crowded.” This suggests early movers who build AI skills now will have significant advantages. The emphasis on agentic AI, LLMs, and practical applications provides a roadmap for aspiring AI professionals, while the success stories validate that multiple pathways—from internal projects to side hustles—can lead to breakthrough opportunities in this rapidly evolving field.
Why This Matters
This article provides crucial insights into the evolving AI job market at a time when artificial intelligence is fundamentally transforming white-collar employment. The consistent emphasis on practical, hands-on experience over formal credentials signals a democratization of AI careers, making the field more accessible to professionals from diverse backgrounds.
The testimonials from successful AI professionals at major tech companies like Google, Microsoft, and Meta validate that self-directed learning and project-based experience can compete with traditional academic pathways. This is particularly significant as AI adoption accelerates across industries, creating unprecedented demand for AI-literate workers.
The article also highlights the financial opportunities in AI contracting, with Shakib earning over $330,000 annually, demonstrating the premium placed on AI skills in today’s market. For businesses, this underscores the importance of providing employees opportunities to work with AI tools and develop relevant competencies. The advice to “get your hands dirty” with AI technology reflects a broader shift toward experiential learning in tech, where demonstrable skills and shipped products increasingly outweigh formal qualifications in hiring decisions.
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Source: https://www.businessinsider.com/tech-workers-simple-tip-for-breaking-into-ai-2025-12