Cassie Chao Leemans

From Hiring Interns to Hiring at 15,000

Her first internship was in New York, on the events team at the Advertising Research Foundation. She had gone in wanting events and marketing. The company's HRBP pulled her in to help hire the next class of interns instead, and that became her first exposure to interviewing and to opening a role. "It was just really exciting to know that you could be a decision maker and help the company find that next set of people to join," she says.

After a year abroad she came back to the United States still thinking her future was in marketing, and took an onsite agency recruiting role at Cisco. She was largely on her own there, working the phones and learning the ropes without anyone teaching her. So she did the most recruiter thing possible: she sourced herself into her next job. She wrote to recruiting leaders at Facebook, at Oracle, at anyone who would answer, with a simple pitch. I want to learn from you.

Oracle and then Palantir followed, both on the university recruiting side she had fallen for. Palantir was her first startup and her first lesson in moving faster, driving faster, building from nothing. Uber was the longest chapter and the defining one. She joined when the company was around 500 people and was the third person on the tech recruiting team. She stayed four and a half years, until Uber was 15,000. From there she went to a 250 person company, following one of her directors of engineering, and then to a 15 person, Sequoia backed startup called Threads, later acquired by Shopify. Each move was a step down in headcount and a step up in influence. Eventually a former manager called with the logical conclusion: you love early stage, that is what we invest in, come do it for 30 or 40 founders at once.

The People She Credits

One of her first hiring managers at Uber was an engineer who genuinely loved recruiting, thoughtful and completely bought into the process. She is candid about where she was in her own development at the time. "I was a yes recruiter. I just wanted to execute, I wanted to hit quota, exceed quota, and just be the best on paper," she says. He taught her when to say no and when to push back. She valued that partnership enough to follow him to Sonder.

At Sonder, Shirley Soon, a former Uber colleague who became her manager, taught her how to manage: how to set expectations, and how to build and hold trust with a team. It also clarified something important about her own shape. Leemans is at her best as a high performing individual contributor, building from nothing and thinking strategically, and she is refreshingly clear that people are built for different things.

The person she calls her career godmother is Teresa Lee, whom she met at Palantir 13 years ago. Lee referred her to Uber. Lee brought her into Sequoia's portfolio. Now that Leemans is in venture, Lee is still her go to. "She has literally guided me through my entire career," she says. She describes one of the hardest working operators she knows, someone who went from Palantir into a very early stage company and built it from the ground up, and who taught her how to hold both herself and her stakeholders accountable in a world where investors are constantly weighing competing demands on their resources.

The last group she credits is the four founders at Threads. They showed her what a real partnership with recruiting looks like when a founder trusts the recruiter they hired to be the subject matter expert. When she told them each of them owed her a minimum of one hour a week in a sourcing jam, and spelled out exactly what output she expected, they buckled down and did it with her, week after week. That consistency, and the willingness of technical founders to sit in the pipeline with her, is the model she now carries into every portfolio conversation.

What She Tells Founders

Her message to the founders she supports is blunt, and it is not the one they expect from a talent partner. Do not hire a recruiter, treat them like a service provider, and assume everything will be fine and dandy at an early stage company. "You need to be just as involved, if not more involved, than your recruiter, because this is your company," she says. "No one's going to sell it better than you as a founder."

She is equally honest about the other side of the equation. Not every recruiter is great, and founders should hold their own ground. But if you are constantly pushing back against someone you hired precisely to do this job, you will not get the outcome you are expecting. Trust, in her framing, is not a soft value. It is the mechanism.

The Wall Is Lower Than It Looks

Four and a half years in venture have shown Leemans a gap. Internal recruiters source and build pipelines, and a wave of tools is being built for exactly that work. On the venture side, where recruiting is chronically underfunded and underbudgeted, almost nobody is building. Maybe one search firm is standing up a CRM, and everyone else wrestles with a legacy system and does the rest by hand. So she built her own.

The hardest part, she says, was never the technology. It was knowing what to ask. Her answer, which she now gives to everyone who asks her the same question, is to ask AI where to start. She uses Whisperflow to talk the problem out loud, describing what her day to day actually looks like and where she is stuck, and lets the model help her frame it. If the answer is over her head, she asks it to dumb it down, to turn it into bite sized pieces. Five months in and building with Claude, she still stops and says she does not understand why a particular suggestion was made, and asks it to explain what is happening on the back end. That, she argues, is how the learning compounds.

An engineer at her firm, a former senior leader at Yahoo, told her plainly that unless she runs into deep technical optimization issues, AI will explain things better than he will, at whatever level she asks for, from high school engineering down to elementary. She has taken that to heart and made it public, posting openly on LinkedIn about what she is building, because she remembers exactly how high the wall looked from the outside. "Don't be afraid," she says. The barrier was never capability. It was not knowing where to begin.

She sees the market moving the same way. Talent engineering roles are appearing: people who can use AI, build out dashboards, and ship their own tooling. And she sees a clear pattern in who is pulling ahead. Those who are open to problem solving, who think critically and stay curious with AI, are the ones launching further and faster in their careers right now. The compounding effect matters to her as much as the individual advantage. A recent exchange with an ex Uber colleague now at Anthropic, ostensibly about references and back channels, handed her a new product feature. She went home and built it.