A Google scientist’s viral story of being recruited by his own employer exposes the algorithmic blind spots and frenzied desperation of the modern AI talent war.

In a telling episode that underscores the chaos of modern tech recruitment, Google recently attempted to poach its own employee. Senior scientist Raj Dabre received a genuine offer to join Google India, seemingly because his absent LinkedIn profile made him invisible to the company’s own recruiting algorithms.

His viral story is more than a humorous blunder; it is a stark symptom of a broken hiring ecosystem. The incident reveals an over-reliance on automated, third-party recruiters who lack basic context, leading to a comical yet profound failure. This occurs against a backdrop of a frenzied AI talent war, where companies blinded by the rush to nab rivals’ experts are somehow overlooking their own. Ultimately, Dabre’s experience serves as a witty caution that in the gold rush for artificial intelligence, we may be neglecting the simple value of common sense.

A Google scientist’s viral story of being recruited by his own employer exposes the algorithmic blind spots and frenzied desperation of the modern AI talent war.

Of all the emails a Google scientist expects to receive, one from Google HR asking if he’d like to work at Google has to be near the bottom of the list. Yet that’s precisely what happened to Raj Dabre, a senior scientist whose story of being poached from himself quickly became a viral symptom of our bizarre tech times. 

This wasn’t a corporate prank or an internal transfer. It was a full-throated recruitment pitch, an offer to join the very company he was already helping to build. The incident, which Dabre shared with a mix of bemusement and grace, is more than a funny blunder. It’s a perfect, almost poetic, reflection of the frantic and often fractured state of Big Tech’s war for AI talent. 

The Accidental Self-Poaching: How Does That Even Happen? 

The story is straightforward. Dabre, who works on machine translation, received a sincere email from a Google recruiter inviting him to explore a role with Google India. His deadpan post on X simply stated: “Google tried to poach me from Google itself.” 

The immediate reaction was a mix of laughter and disbelief. How could a data-driven behemoth like Google not know it already employed one of its own scientists? 

Dabre himself provided the most logical explanation, absolving the recruiter of blame. In a follow-up post, he noted that he doesn’t maintain a LinkedIn profile and hadn’t updated his personal website in some time. “Unless you follow me on Twitter you won’t know where I work,” he wrote. In the eyes of an external recruiting algorithm or a third-party headhunter, he was just another brilliant AI mind waiting to be discovered—even if he was already sitting at his desk in a Google office. 

Beyond the Blunder: A Symptom of a Broken System 

The humor of the situation is a thin veil over a much more serious issue. Dabre’s story is a microcosm of a hiring ecosystem that is increasingly automated, outsourced, and desperate. It suggests that: 

• Resume-Screening AI is No Substitute for Human Context: Companies rely on algorithms to scrape the web and identify potential candidates. When a key piece of data—like current employment—is missing from the usual sources (LinkedIn), the system fails spectacularly. It lacks the basic common sense to cross-reference an internal directory. 

• The “Spray and Pray” Approach to Recruitment: In the scorching-hot AI job market, recruiters are under immense pressure to cast a wide net. The strategy can sometimes seem to be to contact everyone with a relevant keyword in their bio, with only a superficial check to see if they might already be on the payroll. 

• The Third-Party Disconnect: Many large firms use external agencies for recruitment. These agencies operate with a limited view of a company’s full internal structure, making such errors more likely as they aggressively pursue targets on a spreadsheet. 

As one commenter on Dabre’s post astutely observed, “We might see AGI before we see tech organisations fixing their hiring process.” 

The Frenzy Behind the Fumble: The $100 Million Talent War 

To understand why this happened, you have to understand the context. The race for AI supremacy is not a polite marathon; it’s a frantic gold rush where the gold is human intellect. 

The competition for top AI researchers has reached a fever pitch, with staggering figures being thrown around: 

• Meta has reportedly offered signing bonuses and compensation packages reaching into the tens of millions of dollars to lure top engineers. 

• Microsoft is leveraging its startup-like culture, led by AI veterans, to attract talent away from its rivals. 

• Google itself has been both a hunter and the hunted, losing key minds while also spending billions on “acqui-hires” (buying companies primarily for their talent, like the $2.4 billion purchase of Windsurf). 

This isn’t just hiring; it’s a high-stakes poker game where the chips are the people who will define the next era of technology. In such a frenzied environment, it’s almost predictable that the lines between internal and external would eventually blur. The pressure to find the next great mind is so intense that companies are sometimes forgetting to look at the ones already in the room. 

The Human Takeaway: More Than Just a Laugh 

While Raj Dabre’s story gives us a much-needed laugh, it offers a genuine moment of human insight into the modern workplace. 

It’s a reminder that in our pursuit of advanced, world-changing artificial intelligence, we might be overlooking the value of basic human intelligence and simple, integrated systems. It highlights the paradox of a tech industry that builds incredibly complex networks for the world yet can sometimes fail at the simple task of knowing who its own employees are. 

Ultimately, the tale of Google poaching Google is a humorous but cautionary footnote in the history of the AI boom. It tells us that before we can build machines that think like humans, we might need to ensure our own systems haven’t forgotten how to think for themselves.