Rajesh Sura

Rajesh Sura

Head of Data Engineering & Analytics - North America Stores Amazon

Rajesh Sura is a distinguished data and AI leader with over 15 years of experience designing and leading enterprise-scale data platforms, advanced analytics systems, and AI-powered decision intelligence solutions. As the Head of Data Engineering and Analytics at Amazon North America Stores, he spearheads foundational infrastructure powering strategy, automation, and reporting for thousands of users across Amazon’s global ecosystem. Rajesh’s career journey reflects deep expertise across data architecture, cloud computing, artificial intelligence, business intelligence, and external data integration. From orchestrating cloud-native BI transformations to launching NLP-driven analytics and governance frameworks, he has consistently delivered scalable solutions that unlock value and ensure compliance across complex enterprise environments. A Senior Member of IEEE, Fellow at multiple global scientific societies, Rajesh is also a Board Advisor at the AI Frontier Network, GAFAI, and the Intelligent Automation Forum. He serves as a global mentor on ADPList, regularly peer-reviews (>100 manuscripts) for top-tier journals including Springer and Elsevier, and has judged several international hackathons and technology leadership awards. As an independent researcher, keynote speaker, and thought leader, he contributes extensively to the global data community through publications, speaking engagements, and advisory roles. Rajesh holds a strong commitment to mentorship, ethical innovation, and building intelligent analytics systems that are not only powerful, but responsible. Whether leading enterprise-scale transformations or guiding the next generation of talent, Rajesh brings clarity, depth, and a passion for advancing the future of data and analytics.

Agenda Day 1

3:20 PM PRESENTATION: Scaling Agentic AI: Orchestration and Governance in Enterprise Ecosystems


  • From Experimentation to Impact: Shifting from pilot projects to production-grade adoption, driving measurable business outcomes and cultural readiness.
  • Governance & Compliance Frameworks: Building resilient guardrails, trust mechanisms, and audit-ready governance models to align with regulatory and ethical requirements.
  • Enterprise-Scale Orchestration: How to design and manage agentic AI ecosystems that seamlessly integrate multi-agent systems with enterprise workflows, ensuring scalability and performance.