Here's the uncomfortable thing nobody at career services will tell you: "I use Claude every day" stopped being a resume line about six months ago. The people hiring at Amazon, Google, and the frontier AI labs already assume you do. So what actually gets you hired in 2026?

I sat down with Surya Kari, a Senior Generative AI Data Scientist at Amazon, to find out.

Surya works on Amazon's white-glove GenAI team. His days are spent shipping with Fortune 500 customers and the frontier model labs you read about on Twitter. He's in the room when hiring decisions get made. And his honest read on early-career AI hiring is way more specific than the LinkedIn-thinkpiece version.

We start with the thing I keep seeing destroy promising careers: using Claude (or any AI tool) like glorified autocomplete. Surya calls this the fastest way to plateau in your twenties. The fix isn't more tools — it's depth. The kind of moat that doesn't melt the next time a frontier model ships.

Then we get into agents. Surya doesn't think agentic AI is actually production-ready yet (and yes, he works at Amazon, so he's seen the receipts). We talk about what's still broken, what the hype is missing, and what "agents" will probably mean by the time you graduate.

His own story is pretty wild too. He was running a Canadian startup competing against Amazon Go before he ended up running GenAI deals at Amazon itself. The arc from analyst to startup founder to senior AI scientist is full of stuff that won't show up on a tidy career-advice carousel.

The conversation I'm proudest of comes near the end. Surya grew up in India, studied in Canada, works in the US — and he's watched how each region is building AI from the inside. The contrast between how the East and the West think about AI right now is sharper than I expected. His take on India treating AI as public infrastructure is the kind of thing you don't hear in the usual big tech hiring discourse.

If you're a CS student or new grad trying to figure out where to bet your career in the generative AI era, this one's for you. Surya tells you exactly what he'd do today if he were starting over.

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Connect with Surya:LinkedIn: https://www.linkedin.com/in/suryakari/

⏱ Chapters:00:00 A Day in the Life of a Generative AI Data Scientist01:17 Understanding Customer Personas in Generative AI04:17 Upskilling in a Rapidly Evolving Field06:09 The Contrast of Experience in AI Tools09:33 Navigating Production Code and Testing12:15 The Hype Around AI Agents16:28 The Future of AI Agents and Their Limitations20:56 Surya's Journey: From Analyst to AI Expert23:48 Innovations in Retail Technology24:09 Transitioning to Edge Computing and AI26:36 Upskilling in Data Science and AI31:39 Cultural Differences in AI Development36:10 AI as Public Infrastructure in India