Secure Generative AI Apps with Amazon Bedrock + Guardrails + IAM

Secure Generative AI Apps with Amazon Bedrock + Guardrails + IAM 🚀

Generative AI is transforming how applications are built, but without the right security controls, AI systems can expose sensitive data, generate unsafe responses, or provide unauthorized access to powerful models. Building AI applications securely requires more than just deploying a model—it requires strong governance, access control, and responsible AI safeguards.
Join us as we explore how to build secure and trustworthy Generative AI applications using Amazon Bedrock, Guardrails, and AWS IAM. We will break down how to control access to foundation models, protect sensitive information from being exposed, and implement safety controls that help ensure AI responses align with business and security requirements.
Whether you're a DevOps Engineer, Cloud Architect, AI Engineer, Security Professional, or just beginning your cloud and AI journey, this session will provide a practical roadmap for securing Generative AI workloads on AWS. 🤖☁️
📅 Date: June 6th, 2026
⏰ Time: 6:00 PM – 7:00 PM WAT
📍 Location: Virtual

Meet Our Speakers
🎤 Speaker: Abdullateef Ogundipe – AWS Community Builder
🎤 Moderator: Habeeb Babasulaiman – DevOps Engineer

✅ This session will cover:
🛡️ Securing Access to AI Models — Learn how to use AWS IAM to enforce least-privilege access, ensuring users and applications can only interact with the Amazon Bedrock models they are authorized to use.
🚧 Implementing Amazon Bedrock Guardrails — Discover how to apply content filtering, topic restrictions, sensitive information protection, and responsible AI controls to reduce harmful or unwanted model outputs.
🔐 Protecting Sensitive Data in AI Workloads — Understand how to prevent confidential business data and personally identifiable information (PII) from being exposed through prompts, responses, and application integrations.
⚡ Building Production-Ready AI Applications — Explore practical patterns for integrating Bedrock securely into enterprise applications while maintaining compliance, governance, and operational visibility.
🛠️ Real-World Security & Governance Practices — Learn how organizations monitor AI usage, audit access, enforce policy controls, and implement security best practices for Generative AI at scale.