Adam Rousseau

From Accidental Hire to Technical Specialist

The accident stuck because the work turned out to suit him. "I completely fell into it, but also started to really love it," Rousseau says, describing the pull of connecting with people, learning their backgrounds, and understanding the work they had done. That instinct, more anthropological than transactional, has been the through line ever since.

The path since has covered a wide swath of the industry. He worked the agency side. He spent time at Uber recruiting for self-driving, one of the hardest technical talent markets of its era. Then came Duolingo, where six years of building took him across nearly every function a technology company has: hardware, software, finance, product management, and anything touching AI and data science. It is an unusually broad portfolio for a technical recruiter, and it explains why his read on talent markets tends to be structural rather than requisition by requisition. He has seen enough different profiles, in enough different market conditions, to recognize the patterns.

As the founding engineering recruiter at Duolingo, Rousseau did not inherit a playbook. He built one, in partnership with the company's most senior technical leaders, at a moment when the company was scaling into one of the most recognizable consumer technology brands in the world.

The People Who Sharpened Him

Ask Rousseau who shaped him and he divides the answer neatly: one person from the recruiting side, one from the business side.

The first is Renee Davis, now senior director of tech recruiting at Engine, who he reported to and who he first met when she was working university recruiting and he was in sourcing. What began as a working relationship became a friendship and then a standard. "I like the way that she thought about talent and kind of her motor and her drive," he says. She challenged him constantly, pushed him to think differently, and made betterment a daily habit rather than an annual goal.

The second is Natalie Glantz, Duolingo's chief engineering officer, who Rousseau calls a phenomenal partner from the day he started through six years of building together. She gave him something most recruiters never get close enough to see: how the C-suite actually thinks, how change gets made, and how to drive it effectively. She was also never afraid to give constructive criticism, and, just as importantly, never afraid to take it. "We view each other as partners, which I really value," he says. That equality of standing between recruiting and engineering leadership is rarer than it should be, and Rousseau treats it as the model.

He also credits Vince Volpe, senior director of recruiting at Anduril, as a strong partner and the person who hired him at Uber, an early bet that opened the door to the technical recruiting work that has defined his career.

AI as a Tool Belt, Not a Replacement

Rousseau is not an AI skeptic. He uses it daily, defaulting to Claude to brainstorm, to think through problems, to pressure test a new interview rubric, to analyze data, and to understand the competitive landscape he is recruiting against. He has watched it compress work that used to take days: building a sourcing strategy, mapping a talent market, decoding an unfamiliar candidate profile.

But he draws a hard line between augmentation and substitution. "It shouldn't replace the great person and critical thinker that you are," he says. "Because at the end of the day, it's still not perfect." His argument is not sentimental, it is operational. The candidate experience, the thing that ultimately decides whether great people say yes, comes down to a personal touch point that no model has yet learned to fake. Efficiency is available to everyone. Judgment and warmth are not.

It is a balanced position from someone with more standing than most to hold it, having spent years recruiting the very AI and data science talent building these systems.

Be Authentic, Be Curious

Rousseau's advice to other talent leaders comes in two parts, and he is emphatic about both.

The first is authenticity. "I'm myself 24-7," he says, and he works to create a safe space for his team to be themselves too. His reasoning is practical: candidates can tell, and so can the people who work for you. Performance is exhausting and it is transparent.

The second is curiosity, delivered as a warning against reflexive dismissal. "Don't shoot things down just because you don't understand it," he says. See what different tools are offering. Understand why something may or may not work. He points out that a tool demoed and rejected two years ago may have evolved into the exact answer to today's problem, and that the rejection often had less to do with the product than with whether the company or the team was ready for it. Leaders who stay curious, he argues, start to see patterns: what actually matters, and what actually keeps working. Leaders who default to "AI is going to take everything that we have" see nothing at all.

The Next Chapter

After six years, Rousseau closed out his run at Duolingo and went deeper into the AI space, moving cities and coasts to do it, and he is now Talent at Cursor. It is a deliberate choice from someone who has spent his career next to the engineers building the future rather than at a safe distance from them. "It should be an exciting ride," he says.

For a recruiter who once admitted he had no idea what engineers did, it is a fitting arc: a career built entirely on the willingness to walk toward the thing he did not yet understand.