Technical AI Leader · Principal Generative AI Solutions Architect · AWS

Mani
Khanuja

Expert on scaling autonomous AI agents safely & efficiently, AI governance, and strategic leadership.

With 20+ years of experience, Mani builds Generative AI strategy for enterprise customers at AWS. Her current focus is scaling autonomous AI agents safely and efficiently, from building AI platforms from scratch to governing agentic systems at scale. Researcher, author, and speaker sharing insights in the Agentic Enterprise newsletter.

Agentic AI RAG LLMs Context Engineering Amazon Bedrock Distributed Training
Mani Khanuja
20+Years in AI & Technology
About

Architecting the
Future of AI

Mani Khanuja is a Technical AI Leader and Principal Generative AI Solutions Architect at AWS with 20+ years of experience building AI platforms from scratch and driving enterprise AI strategy. She works directly with customers to build their Generative AI strategy, from architecture to production deployment at scale.

Her current focus is scaling autonomous AI agents safely and efficiently: developing stateful, memory-driven agents with personalization, advancing AI governance frameworks, and translating cutting-edge research into real-world enterprise systems. She is the author of Applied Machine Learning and High-Performance Computing on AWS and co-author of the upcoming The AI Steering Wheel.

A pioneering researcher, she co-authored the widely cited paper "Keyword search is all you need: Achieving RAG-level performance without vector databases using agentic tool use." She is also a recognized technical speaker at Re:Invent, Grace Hopper Celebration, AI Engineer Summit, and AWS Summits worldwide. She resides in Seal Beach, California, where she stays active with long runs along the coast.

Mani Khanuja
20+
Years of Experience
10+
Conferences
2
Books
12+
Papers Reviewed
Gallery

On Stage & In the Field

Mani Khanuja on air at AWS Re:Invent
AWS Re:Invent On Air
Mani Khanuja speaking at AWS Summit Toronto on High-Performance Model Deployment with SageMaker
AWS Summit Toronto: High-Performance Model Deployment with SageMaker
Mani Khanuja at Grace Hopper Celebration 2023
Grace Hopper Celebration 2023
YouTube

Featured Talks & Sessions

Deep-dives on Agentic AI, RAG, Amazon Bedrock, distributed training, and more, top videos by views.

View Full Playlist on YouTube →
Writing

Newsletter & Articles

Insights on Agentic AI, ethics, enterprise deployment, and the future of autonomous systems, from the Agentic Enterprise newsletter.

All Articles on Substack LinkedIn Newsletter
AWS Machine Learning Blog

AWS Blog Posts

Technical deep-dives published on the AWS Machine Learning Blog.

AWS Machine Learning Blog · 2025
Amazon Bedrock AgentCore Memory: Building Context-Aware Agents
A deep-dive into Amazon Bedrock AgentCore Memory, how to build AI agents that maintain context across sessions, enabling genuinely personalized, stateful interactions that improve over time in enterprise deployments.
Read
AWS Machine Learning Blog · 2026
Build Agents to Learn from Experiences Using Amazon Bedrock AgentCore Episodic Memory
A technical walkthrough on building AI agents with episodic memory, enabling agents to retain context across sessions, learn from past interactions, and deliver personalized responses at enterprise scale using Amazon Bedrock.
Read
AWS Machine Learning Blog · 2025
Streamline GitHub Workflows with Generative AI Using Amazon Bedrock and MCP
Explore how the Model Context Protocol (MCP) connects Amazon Bedrock to GitHub, enabling AI agents to automate pull request reviews, issue triage, and code generation workflows, reducing developer toil and accelerating delivery.
Read
AWS Machine Learning Blog · 2025
Unlocking the Power of Model Context Protocol (MCP) on AWS
A comprehensive guide to MCP on AWS, how the Model Context Protocol enables AI agents to securely connect to data sources, tools, and APIs. Covers architecture patterns, security considerations, and practical implementation with Amazon Bedrock.
Read
AWS Machine Learning Blog · 2025
From Concept to Reality: Navigating the Journey of RAG from Proof of Concept to Production
Bridges the gap between RAG prototypes and production-grade deployments on AWS. Covers chunking strategies, retrieval optimization, evaluation frameworks, and the architectural decisions that determine success at scale.
Read
AWS Machine Learning Blog
Create a Next-Generation Chat Assistant with Amazon Bedrock, Connect, Lex, LangChain, and WhatsApp
Step-by-step guide to building a production-ready conversational AI assistant that combines Amazon Bedrock's foundation models with Amazon Connect and Lex for omni-channel customer engagement over WhatsApp.
Read
Books

Published Works

From high-performance computing to the agentic frontier, bridging theory and enterprise practice.

Applied Machine Learning and High-Performance Computing on AWS book cover
Published

Applied Machine Learning and High‑Performance Computing on AWS

A comprehensive guide to building, training, and deploying ML models at scale on AWS. Covers distributed training, feature stores, SageMaker, and production ML pipelines for enterprise workloads. Co-authored with Farooq Sabir, Shreyas Subramanian & Trenton Potgieter.

Get on Amazon
The AI Steering Wheel book cover
Upcoming

The AI Steering Wheel

Unified Framework for Scaling Generative and Agentic Systems

Three interlocking layers, Strategy, Operations, and Engineering, keep AI products aligned from the first decision through the last deployment. Co-authored with Dr. Fouad Bousetouane.

Research

Research & Publications

Peer-reviewed papers advancing retrieval-augmented generation, agentic systems, and applied machine learning.

Keyword Search is All You Need: Achieving RAG-Level Performance Without Vector Databases Using Agentic Tool Use
Mani Khanuja et al. · arXiv · arXiv:2602.23368
Demonstrates that agentic tool-use with traditional keyword search can match or exceed vector database retrieval in RAG pipelines, with significant cost and complexity advantages for enterprise deployments.
Read Paper
The Amazon Nova Family of Models: Technical Report and Model Card
Amazon · arXiv · arXiv:2506.12103
Presents Amazon Nova, a new generation of state-of-the-art foundation models delivering frontier intelligence and industry-leading price performance, including Nova Pro (multimodal), Nova Lite, Nova Micro, Nova Canvas (image generation), and Nova Reel (video generation). Covers benchmarking, agentic performance, long context, and safety.
Read Paper
Peer Reviewer · WACV 2024, IEEE/CVF Winter Conference on Applications of Computer Vision
Primary Reviewer · 10,12 Papers Reviewed
Served as a primary reviewer for IEEE/CVF WACV 2024, contributing expert evaluation to advance the computer vision research community.
Peer Review
Speaking

Conference Appearances

Keynotes, deep-dives, and technical sessions at leading industry events worldwide.

AWS Re:Invent
2021 · 2022 · 2023 · 2024 · 2025
Grace Hopper
GHC 2023
AI Engineer
Summit 2025
AWS NY Summit
New York 2025
Women in West
2022
+ Many More
Worldwide
Invite Mani to Speak Watch Past Talks
Stay Connected

Follow the Agentic
Enterprise Journey

Get the latest thinking on Agentic AI, research, and enterprise ML delivered directly to you.