AI-powered software engineering agents are rapidly evolving from code assistants into autonomous collaborators capable of writing code, reviewing pull requests, executing tests, provisioning infrastructure, and even participating in deployment workflows. While these capabilities promise unprecedented improvements in developer productivity, they also introduce new cybersecurity challenges that traditional application security programs were never designed to address.

This session explores how organizations can securely adopt AI engineering agents without compromising governance, compliance, or operational resilience. Attendees will learn the architectural principles behind building trustworthy AI agents, including identity and authentication, least-privilege access, secure tool invocation, prompt injection defenses, data protection, policy-as-code, human approval workflows, audit logging, and continuous monitoring.

Rather than focusing on a specific vendor or AI model, this presentation presents a practical enterprise reference architecture that can be applied across cloud platforms and development ecosystems. Through real-world scenarios, participants will examine how AI agents interact with source code repositories, CI/CD pipelines, infrastructure automation, and internal engineering tools, while understanding the security controls required to prevent unauthorized actions, data leakage, supply chain compromise, and abuse of privileged capabilities.

Attendees will leave with a comprehensive governance framework, implementation roadmap, and actionable best practices for deploying AI engineering agents responsibly at enterprise scale. Whether your organization is beginning its AI journey or expanding autonomous software delivery, this session provides practical guidance for enabling innovation while maintaining security, transparency, and organizational trust.