Four Google Professionals on Their Journey to AI Roles

Adopting the AI label in today’s job market is certainly trendy, but achieving such a transition requires significant effort.

With AI job offerings expanding and companies pouring resources into skills development, employees are eager to incorporate AI into their careers. Business Insider engaged in conversations with four Googlers who successfully made this transition. Each one blazed a unique trail, yet all invested approximately twelve months prepping for their new positions—some took even longer.

The Story of Emrick Donadei

Emrick Donadei, at 32, transformed his career trajectory after a pivotal experience at a week-long internal hackathon at Google in 2024. Although he didn't create a groundbreaking product, the exposure to AI tools provided invaluable knowledge and a conversational icebreaker with various teams.

Approximately ten months following his hackathon involvement, Donadei secured a new position. But his pursuit of AI mastery extended beyond this event. He dabbled with AI tools personally, started an AI-focused podcast, and immersed himself in learning from Andrej Karpathy's YouTube channel on machine learning, LLMs, and more.

He benefitted from participating in another hackathon in 2025, unlocking more avenues, such as AI research projects and roles on open-source and research teams. Additionally, he published a Google technical disclosure, complementing his practical experience.

Maitri Mangal’s AI Transition

Transitioning from a conventional software engineer to an AI role, 27-year-old Maitri Mangal allocated two hours daily to enhance her skills over a year. The habit continues, with weekly learning sessions still part of her routine.

For Mangal, creating digital content wasn't just a way to weave in knowledge from Google’s internal sessions and online courses; it became a turning point in her educational journey.

Empowered by the positive impact of her work on others, she maintained momentum and still dedicates an hour daily to absorbing new knowledge through internal resources and online courses, even after switching her role.

Rahul Kasanagottu: From Reading to Realization

Rahul Kasanagottu took over two years to pivot into his AI-focused role at Google, leveraging his paternity leave to delve into AI literature.

His early dive included perusing eleven books, participating in Andrew Ng’s Deep Learning Specialization, and tuning into 3Blue1Brown's explanatory videos.

Kasanagottu highlighted the necessity of practical projects in demonstrating his AI proficiency during job applications. The absence of assignments in his chosen books contrasted with the course’s hands-on focus, which he found crucial.

Milica Cvetkovic: A Pathway from Academia to AI Consulting

Milica Cvetkovic found her niche in AI consulting at Google around three years ago, following advanced studies and research in machine learning.

Armed with a Master’s in statistics, she worked at a startup, instructing machine learning courses concurrently with engineering roles. Her ability to explain complex ideas simply became her standout asset.

For Cvetkovic, landing at Google was less about an active switch and more about seizing an opportunity that aligned with her academic and professional path, coinciding with the realization that coding wasn’t her passion anymore.

Her journey to AI consulting is akin to marathon training—her application represented a culmination of extensive prep work.