AWS Generative AI Architect
Generative AI on AWS is no longer just a model invocation problem. Production systems need retrieval, agents, tools, identity, guardrails, evals, observability, cost controls, deployment discipline, and human escalation.
This talk gives senior developers and architects a practical blueprint for becoming an AWS Generative AI Architect. We will explore how to design production-ready AI systems using Amazon Bedrock, Bedrock Knowledge Bases, Bedrock Agents, AgentCore, Guardrails, Evaluations, Lambda, API Gateway, Step Functions, EventBridge, OpenSearch, S3, DynamoDB, IAM, CloudWatch, and related AWS services.
The goal is not to memorize AWS service names. The goal is to learn how to design reliable, secure, measurable, cost-aware, and governable AI systems on AWS.
The hard part of AWS generative AI is no longer model access. The hard part is designing the system around the model: evidence, tools, identity, guardrails, evals, observability, cost, and safe action.
Learning outcomes
Participants will learn how to:
- Explain the architecture shift from model invocation to production AI systems.
- Design a production RAG architecture using Amazon Bedrock and AWS data services.
- Design safe agentic workflows using Bedrock Agents and AgentCore concepts.
- Apply guardrails to inference, agents, and knowledge-base workflows.
- Define evals for model quality, retrieval quality, groundedness, tool safety, and regression.
- Design observability for prompts, retrieval, tool calls, traces, latency, errors, and cost.
- Apply IAM, identity, secrets, data boundaries, and least privilege to AI systems.
- Control cost and latency through model selection, prompt design, caching, routing, quotas, and workflow design.
- Recognize anti-patterns in AWS generative AI architectures.
- Map production architecture skills to AWS Generative AI Developer – Professional readiness.
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of Architecture working at Salesforce. Rohit has extensive experience architecting multi-tenant cloud-native solutions in Resilient Microservices Service-Oriented architectures using AWS Stack. In addition, Rohit has a proven ability in designing solutions and executing and delivering transformational programs that reduce costs and increase efficiencies.
As a trusted advisor, leader, and collaborator, Rohit applies problem resolution, analytical, and operational skills to all initiatives and develops strategic requirements and solution analysis through all stages of the project life cycle and product readiness to execution.
Rohit excels in designing scalable cloud microservice architectures using Spring Boot and Netflix OSS technologies using AWS and Google clouds. As a Security Ninja, Rohit looks for ways to resolve application security vulnerabilities using ethical hacking and threat modeling. Rohit is excited about architecting cloud technologies using Dockers, REDIS, NGINX, RightScale, RabbitMQ, Apigee, Azul Zing, Actuate BIRT reporting, Chef, Splunk, Rest-Assured, SoapUI, Dynatrace, and EnterpriseDB. In addition, Rohit has developed lambda architecture solutions using Apache Spark, Cassandra, and Camel for real-time analytics and integration projects.
Rohit has done MBA from Babson College in Corporate Entrepreneurship, Masters in Computer Science from Boston University and Harvard University. Rohit is a regular speaker at No Fluff Just Stuff, UberConf, RichWeb, GIDS, and other international conferences.
Rohit loves to connect on http://www.productivecloudinnovation.com.
http://linkedin.com/in/rohit-bhardwaj-cloud or using Twitter at rbhardwaj1.