Hiring data and AI leaders for India's Global Capability Centres

India's Global Capability Centres have quietly become one of the largest sources of senior data and AI hiring anywhere in the world. They are no longer back offices. They are where multinational companies build product, engineering and, increasingly, their AI capability.

The numbers make the point. According to figures from Zinnov and Nasscom, India now hosts 2,117 GCCs across 3,728 centres, employing around 2.36 million professionals, roughly 45% of the global GCC talent base. Over 90% now operate as multi-functional technology and product engineering hubs, and more than 250,000 AI/ML professionals already work across 250+ dedicated AI centres of excellence.

Why the hiring is harder than the headcount suggests

A large talent pool does not make senior hiring easy. It makes it noisy.

• Titles have inflated. "Lead" and "Principal" mean very different things from one centre to the next. Screening on titles alone produces long shortlists of the wrong people.
• The best people are already busy. Engineers who have taken models to production at scale are rarely looking. They will not see your job post, and they ignore generic outreach.
• GCC roles straddle two organisations. A data leader in a GCC answers to a local site leader and to a global function head, often in another time zone. Candidates who have never worked in that matrix can struggle, however strong their technical record.

“A large talent pool does not make senior hiring easy. It makes it noisy.”

What good GCC data and AI hiring looks like

The searches that go well tend to share three things.

1. A brief written around outcomes, not tools. "Build a feature store the global product teams will actually use" is a better brief than a list of technologies. It tells candidates what success looks like, and it lets you assess them against it.
2. A real market map. For senior roles, the strongest candidates usually sit in a small number of peer GCCs, product companies and well-funded startups. Knowing who has built what, and where, matters more than the size of the database you search.
3. Honest calibration on compensation early. Senior data and AI compensation moves quickly. Agreeing the range at the start avoids losing your preferred candidate at offer stage.

Where to begin

If you are planning to grow a data or AI function in an Indian GCC over the next year, start with the leadership hire. The right head of data science or data engineering will shape every hire that follows, and will make the rest of the team far easier to build.