Manu Agrawal AI infrastructure, healthcare AI, and governed autonomy

Professional CV

AI infrastructure, healthcare AI, and cloud-scale platform leadership.

Selected professional summary of Manu Agrawal's work across AI infrastructure, agentic AI, healthcare AI, cloud platforms, and trustworthy enterprise AI systems.

Summary

Technology leader with 13+ years of experience driving AI, data, and platform transformation across healthcare and cloud. Current work focuses on agentic data, workflows, governance, privacy, trust, and AI platform strategy at Oracle Health.

Previously led technical strategy and execution across large engineering organizations at Amazon Web Services, spanning multimodal AI, inference platforms, cloud edge systems, data platforms, and production distributed systems.

Experience

2025-present
Oracle Health - AI Architect and Gen AI Leader, Agentic, Data, Privacy and Trust

Defines architecture and platform direction for agentic healthcare systems, including multi-agent runtimes, human-in-the-loop coordination, tool catalogs, workflow execution, extraction services, evaluation loops, memory-aware workflows, retrieval systems, and policy-aware execution. Works with NVIDIA and OpenAI teams through formal technical partnership sessions to evaluate integration opportunities for enterprise and healthcare AI systems.

2016-2025
Amazon Web Services - AI, cloud, and distributed systems

Worked across Amazon Bedrock, AWS Rekognition, AWS Textract, CloudFront, Amazon Global Accelerator, and related platform systems. Work included multimodal AI infrastructure, unstructured-to-structured data extraction, inference modernization, data platforms, control planes, edge systems, and highly available distributed architectures.

AWS AI
Amazon Bedrock, Rekognition, and Textract

Led or contributed to multimodal AI initiatives, model-serving foundations, accelerated inference systems, production AI service design, data processing platforms, training-data governance, privacy frameworks, and reusable AI platform components.

AWS Edge
CloudFront and Amazon Global Accelerator

Designed and delivered control-plane, data-plane, propagation, and configuration-management systems supporting high-scale cloud edge infrastructure and production service reliability.

Earlier roles
Parametric Technology Corporation, Amdocs, Ericsson

Worked on enterprise lifecycle management, ordering systems, telecom software, and early software engineering projects before moving into large-scale cloud and AI infrastructure.

Education

Bachelor of Engineering in Information Technology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, India.

Skills

  • Agentic AI systems and multi-agent orchestration
  • Healthcare AI platform architecture
  • AI governance, trust, privacy, and evaluation
  • Distributed systems and cloud control planes
  • Java, Kotlin, Go, Python, SQL, C++, Rust
  • OpenSearch, DynamoDB, Oracle, MySQL
  • Model serving and inference systems
  • Workflow execution and retrieval systems

Service

Professional service spans executive AI roundtables on agent identity and agent development, expert forums, and peer review across AI, machine learning, healthcare, and data venues.

  • Executive roundtables on agent identity, agent development, and governed autonomy.
  • Senior Executive AI Think Tank.
  • Reviewer, ISPOR.
  • Reviewer, ICML AWILD Workshop.
  • Reviewer, COLM Re-Data Workshop.
  • Reviewer, RSMBD Main Conference.
  • Reviewer, MLCCIM Main Conference.
  • Reviewer, COLM DAIH Workshop.
  • Reviewer, Fast Machine Learning for Science Conference 2026.

Scholarly work

Co-author of accepted workshop and scholarly articles in AI and data venues, including KDD and COLM Re-Data. Selected citations will be added as proceedings and publisher pages become public.

Public links