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Sankar Vema

Your instructor

Sankar Vema

Chief Technology and AI Officer, Zettamine

Twenty-five years building, leading and scaling technology. Now teaching engineers to build AI that ships.

Bharat · works with teams globally LinkedIn
25+Years in enterprise tech280+Engineers led15+Systems architected & shippedFortune 500Clients advised

Sankar Vema is Chief Technology and AI Officer at Zettamine and the architect behind GuildTrek. He has spent twenty-five years building, leading and scaling technology for national governments and Fortune 500 enterprises, and now works hands-on in agentic architectures, model design, and AI product development.

Why learn from Sankar

  • Account CTO for AT&T and Zurich Insurance at DXC, and led an engineering organisation of 280+ at Brane, including a 42-strong AI and NextGen team.
  • Has shipped real AI products end to end: agentic assistants, enterprise RAG, industrial computer vision, and GuildTrek itself. Not slideware.
  • Knows exactly where AI work fails: in operations, not in models. Data pipelines, evaluation, monitoring, retraining, and governance, the parts most courses skip.
  • Has hired and scaled engineering teams from the first five to the first fifty, so he knows what an interviewer actually looks for, and builds you toward it.

Worked with

AT&TZurich InsuranceNestléAirbusMastercardJohn DeereCaterpillarHyundaiKONETata JLRPhilips

Why is a leader at this level teaching?

There is a tired notion that training is where a career goes to retire. This is the opposite of that. The gap between what the industry needs and what people are trained on has become the single biggest bottleneck to Bharat leading in AI, and closing it is worth a leader's time.

The ethos is simple: the useful part is the design, the judgment, and giving that judgment away. No selling, just an honest diagnosis of what will actually make you capable. You get a practitioner who still builds, teaching the parts he wishes someone had taught him.

How he thinks about the work

  • Architecture is a series of bets, not a diagram.
  • AI work fails in operations, not in models. Build for the second year, not the demo.
  • Ship the thinnest end-to-end version first.
  • Build for the team you will have, not the team you have.