Expedia Opens San Jose AI Hub to Recruit From Big Tech's Backyard

Why Expedia Built an AI Hub Minutes From Google

Expedia has planted a new AI and machine learning engineering outpost on North First Street in San Jose, less than 10 miles from Google’s Mountain View headquarters. The location deliberately places the online travel giant in the same recruitment pool as Google, Cisco, Adobe, PayPal and eBay as it tries to hire specialists who can turn AI into tools travelers and partners actually use.

Chief Technology Officer Ramana Thumu frames the office as an execution play. Every major travel brand is talking about AI, but the real constraint is engineering capacity. Thumu said hiring delays can stretch a 12-month AI project timeline to 18 months, a gap he describes as an eternity in AI development. The hub was designed with that recruitment problem in mind.

The company is also making a cultural pitch. Julia Elliott, Expedia Group’s vice president of technology and chief of staff to the CTO, left Google after a decade to join in January. Her stated reason is that travel has “interesting problems to solve,” suggesting Expedia hopes mission complexity, not just compensation, can pull engineers away from larger platforms.

For now, the hub is a bet: proximity to Big Tech’s talent density could shorten Expedia’s hiring cycles, but it also puts the company in direct competition with some of the deepest-pocketed employers in the world.

The Talent Math Behind Expedia's Silicon Valley Push

Expedia’s location bet on colocated AI work

The San Jose office is not simply a real estate decision. Expedia is placing machine-learning engineers and product teams close to the concentration of AI researchers, infrastructure engineers and product talent around Silicon Valley. The calculation is that shorter hiring cycles matter more than distributed remote hiring when internal plans are measured in 12-month product windows. If CTO Ramana Thumu is right that delayed hires can stretch those windows to 18 months, then every month saved in recruitment has direct product value.

Google, Cisco and the talent pool Expedia is entering

With North First Street located less than 10 miles from Google’s headquarters, Expedia is deliberately hiring from the same pool as Google, Cisco, Adobe, PayPal and eBay. The practical consequence is that Expedia will have to match or offset Big Tech compensation, equity and infrastructure budgets for AI staff. That is a meaningful cost shift for a travel marketplace operator whose business is also exposed to travel demand cycles. The upside is access to engineers already trained on large-scale AI systems; the risk is paying Big Tech rates without Big Tech AI scale.

An alternative interpretation is that Expedia is not trying to outbid Google on every hire. The office may be targeting engineers who want a smaller team, clearer product ownership or a break from platform-scale monotony. But the company has not disclosed headcount, pay bands or the specific products the hub will own, so the size of that pool remains uncertain.

What Julia Elliott’s move says about the pitch

Elliott’s shift from a decade at Google to Expedia gives the recruitment story a named proof point. The public reason is travel’s problem complexity: search, inventory fragmentation, personalization, payments and customer service all meet in a single transaction. If that pitch resonates, Expedia may pull senior staff who want more end-to-end ownership. If it does not, the office could fill with mid-level engineers while senior AI talent stays at platform companies. The first 12 to 18 months of hiring will show which direction the hub takes.

What Expedia's AI Hiring Move Signals for Travel Tech

• For Expedia product and engineering leaders, Thumu’s 12-to-18-month timeline warning means staffing targets for the San Jose hub should be tied to AI feature release milestones, not treated as a separate HR metric.
• For competitors in online travel, the San Jose location signals that AI execution is being fought over engineering capacity, not just announcements. Compare your AI recruitment reach against the North First Street hiring pool — Google, Cisco, Adobe, PayPal and eBay — to see whether your open roles can be filled locally at comparable speed.
• For AI specialists weighing Expedia, Elliott’s rationale offers a concrete checklist: travel search, fragmented inventory, personalization, payments and service. The pitch only pays off if the role provides end-to-end accountability for one of those domains rather than a narrow platform component.
• For Expedia’s management, the unstated detail is compensation. Hiring in the same pool as Google and Cisco requires sustainable Bay Area AI pay; board-level scrutiny should focus on whether that cost can be absorbed without squeezing travel product budgets.