Sand Hill's sharpest eye on the AI infrastructure stack - and she can also pour a mean latte.
She wrote backend code at Google for five years. Then she left for Stanford. Then she wrote checks at a16z. The path looks linear only in retrospect.
There's a specific kind of investor that makes founders stop mid-pitch. Not because they're famous or because they lead bigger rounds - but because they understand what you actually built. Malika Aubakirova is that investor. She spent five years inside Google's infrastructure before anyone considered paying her to evaluate other people's.
At Chronicle Security - Alphabet's Moonshot Factory attempt at rethinking cybersecurity - she didn't just ship features. She drove Rules Engine to general availability and helped launch Chronicle Detect. These are not glamorous products. They are the kind of products that keep security operations centers sane at 3am. Knowing how hard they are to build is what makes her qualified to bet on the next generation of them.
"I just didn't want to keep still."- Malika Aubakirova
The Stanford MBA was the pivot that was not really a pivot. It was an upgrade. In two years at the Graduate School of Business, she moved from never having considered venture capital to closing investments at Andreessen Horowitz, one of the most consequential firms in technology. She was a Scout at Greylock, a Venture Investor at Stanford's GSB Impact Fund, and a Principal In Residence at MVP Ventures - all before collecting her degree.
At a16z she sits on the AI Infrastructure team, which means she is paid to think about the layer of technology most investors still treat as plumbing. The AI model gets the headline. The infrastructure that makes it reliable, secure, and cost-effective at scale is what Aubakirova is watching. She has co-authored research covering how 100 trillion AI tokens actually move through real systems. That is not a soft focus area. That is a thesis.
Her Stanford Daily profile called this her "second act." She seems unbothered by the framing - and probably already has a third act in mind.
Aubakirova's investment thesis centers on the companies building what AI needs to be reliable, secure, and deployable at scale - not the models, but the stack underneath them.
Astana in the 1990s was not a soft environment. Kazakhstan had just become independent, the Soviet infrastructure was crumbling, and the economy was in freefall. Malika Aubakirova grew up there - a first-generation immigrant in the making, though she didn't know it yet.
She has described traveling alone on Kazakhstani buses as a child with an oversized backpack. The older women on those buses offered disapproval, not assistance. She figured it out herself. That is not a metaphor she uses to explain her success. It is a literal description of how she learned to navigate systems that were not designed to help her.
When she arrived in the United States and made it to the University of Chicago, she graduated with honors in Computer Science and Economics - two ways of modeling the world. Then she went to Google and spent five years learning how the world's largest distributed systems actually work at scale. Not from textbooks. From production.
"You can't coast in that environment."- Malika Aubakirova
The Stanford MBA was not a retreat from engineering. It was a deliberate acquisition of a different tool: fluency in capital allocation. She arrived knowing how to build. She left knowing how to bet. The combination is rarer than either piece alone.
The double major wasn't accidental. Systems design and incentive design are the same discipline viewed from different angles. She learned both before most people pick one.
Used the MBA not as a credential but as an operating system upgrade. Praised GSB's emphasis on vulnerability and self-awareness alongside the rigorous academics.