JingJing (Chris) Bao
Senior Software Engineer
Beijing, China
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I am JingJing (Chris) Bao, a senior software engineer currently working at Schlumberger. Previously worked in the software division of ASML and Grab, with 10 years of cross-industry R&D experience spanning semiconductors, internet, and energy.
Specializes in AI/ML systems, scalable distributed architecture, real-time computing and visualization, and high-concurrency programming, with deep experience in integrating AI with software engineering and turning it into production-ready solutions.
Holds the Microsoft Azure AI certification as a technical expert and is also a Microsoft Certified Trainer, with long-term dedication to technical knowledge sharing and talent development
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Topics
AI Gateway as a Security Control Plane: Content, Access, and Operational Controls
As AI applications move from experimentation into production, security teams need more than model-level safeguards. They need a control plane that can enforce policy consistently across prompts, agents, tools, and model endpoints. This session presents the AI gateway as that control plane.
I’ll walk through a practical gateway-based security architecture built around three layers of control for production AI systems:
- Content controls inspect and block risky requests and responses, including prompt injection attempts, unsafe content, and sensitive data exposure.
- Access controls govern which users, apps, agents, and MCP tools can reach model and API endpoints through authentication and authorization policies.
- Operational controls provide the limits, monitoring, and enforcement mechanisms needed to keep AI workloads safe, reliable, and manageable at scale.
Using Azure API Management and Azure Content Safety as the implementation example, this session shows how these controls work together in a real deployment. Let’s discuss how to reduce AI risk, apply stronger enforcement at the gateway layer, and build safer AI applications for production use.
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