Want to break into VC in 2025? MBAs and consulting backgrounds are out. Technical skills, especially AI, are in.

Deedy Das (left), a principal at Menlo Ventures, held senior engineering roles at Glean, Facebook, and Google. Jon Chu, a partner at Khosla Ventures, previously worked as an engineer at Palantir and built machine learning at Facebook. 

Matt Hoffman, head of talent at M13, an early-stage venture firm, is preparing to hire a new junior investor sometime next year. As recently as a year ago, he would have sought out someone from a top business school or consulting firm. Now, he wants someone with deep technical expertise.

“The technology is just getting really sophisticated,” Hoffman said. “You need to have enough sophistication to be able to understand the tech you are assessing.”

As venture firms struggle to raise new funds, they have been hiring fewer roles and even shedding staff. On rarer occasions when they are hiring, they are increasingly seeking out candidates with deep domain expertise, especially in artificial intelligence.

“We certainly noticed it in the past 3 to 6 months, and like a lot of VC, once it kind of takes momentum, it snowballs, and all the other VCs are doing it,” Hoffman said. “The traditional MBA background will not be sufficient for the best investors going forward.”

Evaluating previous generations of startups required less sophistication, according to Deedy Das, who this year was hired as a principal at Menlo Ventures, which backs OpenAI rival Anthropic. He previously worked for nearly a decade in senior engineering roles at Facebook, Google, and Glean, a buzzy AI-powered search startup valued at $4.6 billion.

“To understand Facebook, you don’t need to be technical to get it,” Das said. “You know people go online to use an app and connect with their friends. You can see how it can make money. For AI, if I tell you I have the best model in the world, how are you, as a non-technical person, going to call my BS on that?”

Ben Lerer, managing partner at Lerer Hippeau, says he wants to hire “younger people who are more natively growing up with AI and think about AI as less of a novelty and more of just a sort of inevitability.”

Hiring for the investing theme du jour

Mark Suster, a partner at Upfront Ventures, says he used to recruit from blue-chip consulting firms like McKinsey & Company and Bain & Company, whereas recent hires have all brought specific expertise in areas the firm wants to focus on.

“I don’t think generalist works anymore because venture capital is too competitive now,” said Suster.

“We’re going much deeper in our industries, and so when we went to invest in healthcare, we hired a healthcare expert. Now that we’re doing more semiconductors, we’re trying to get somebody with semiconductor experience. We’re doing more with satellites, so we want someone from day one who understands the customer and the technology.”

Upfront is currently hiring for an investment associate focused on machine learning and AI.

Last year, Khosla Ventures hired John Chu as a partner, who held senior engineering roles at Meta and Opendoor. This fall, Katie Jacobs Stanton, a longtime Twitter insider turned venture capitalist, hired a former engineering leader to her firm, Moxxie Ventures.

Ashwin Lalendran worked on drones at the Air Force Research Laboratory, shipped 3D vision software for Apple’s mapping and self-driving-car projects, and led a team of engineers to scale the world’s largest private-owned network of ocean sensors at Sofar Ocean.

He joins Moxxie’s deep bench of operators to assist with sourcing, evaluating, and closing deals in deep tech, hardware, and national security, areas where Moxxie has deepened its focus over the past year.

Firms have long hired from certain networks based on the investment theme du jour, according to Yoni Rechtman, a principal at Slow Ventures, an early investor in Robinhood and PillPack.

During the fintech boom, Stripe was the hot ticket, and investors rushed to hire from the fintech giant.

Today, firms are chasing after ex-Palantir and OpenAI employees to fill out their ranks — some of them are restaffing after years of hiring slowdowns or job cuts, though such moves remain rare in the venture industry — and to add expertise and networks in their fields of interest.

Slow Ventures is looking to add as many as four associates over the next year based on the quality of talent on the market, Rechtman said. Being technical as an associate is a plus but not a requirement, though. “Being credible with founders because you worked at OpenAI is great,” Rechtman said, “but doesn’t necessarily mean much for your ability to pick stocks well.”

VC firms can’t compete with startups on compensation

Increasingly, venture firms find themselves squaring off with the hottest AI companies to secure top talent, according to Dan Miller, a recruiter and partner at True Search. “For a lot of VC firms, the stiffest competition for talent over the last year has been OpenAI,” said Miller.

He’s worked with several venture firms on partner and principal searches that lost candidates to the ChatGPT-maker. That is largely because OpenAI offers salaries above market rate and a chance to contribute to cutting-edge research and development. Those candidates, in turn, gain experience that opens doors to top-tier venture firms down the line, Miller added.

The average salary for a VC with 1-3 years of experience is $264,000, according to Glassdoor, an anonymous job review site. By contrast, OpenAI’s median yearly total compensation is $534,197, according to Levels.fyi, which tracks compensation data at tech firms and startups.

“No VC will pay what a good AI engineer can make a company,” said M13’s Hoffman. “So our job is to find people who get excited about working in venture and helping to build a number of companies rather than just one.”

Das said he did take a step down in pay when he joined Menlo Ventures after Glean, “but I wasn’t concerned because if this worked, it would be a long-term bet where the comp would be fine,” Das said.

He explained that he was excited to try venture because he was ready for a new challenge and also thought his technical chops would give him an edge over generalist investors evaluating AI infrastructure and machine learning deals.

“I thought a lot of venture capitalists were actually pretty terrible doing diligence on companies that were technical because they weren’t technical.”

Das was recently on a call with co-investors, and they needed his expertise. They were stumped and needed help understanding some of the jargon the founder of an AI startup was using.

“I chuckled because every second pitch I see is some version of fancy technical lingo, which actually doesn’t mean much if you dig into it,” Das said. “That’s something a traditional investor has a really hard time seeing through.”