Ganesh Adepu

Secure LLM Platforms in Java

Abstract:

As Large Language Models (LLMs) rapidly move from experimentation to enterprise-scale production, organizations are increasingly adopting Java-based architectures to integrate, orchestrate, and secure AI-driven systems. However, this shift introduces a new class of security, scalability, and observability challenges that traditional application design patterns fail to address.
In this session, we explore how Java can serve as a robust backbone for building secure, production-grade LLM platforms. We will walk through a reference architecture leveraging Spring Boot, microservices, API gateways, and event-driven pipelines to integrate LLM providers while maintaining strict security and governance controls.
The talk will highlight critical risks such as prompt injection, data exfiltration, insecure output handling, and model abuse, mapping them to emerging standards like the OWASP Top 10 for LLM Applications. Attendees will learn how to implement guardrails including input validation, role-based access control, output filtering, rate limiting, and zero-trust API security.
We will also dive into real-world production lessons, including latency optimization, token cost management, observability using OpenTelemetry, and secure DevSecOps pipelines for AI workloads. Additionally, we will discuss strategies for integrating vector databases for Retrieval-Augmented Generation (RAG) while ensuring data privacy and tenant isolation.
By the end of this session, participants will gain actionable insights, architecture patterns, and security best practices to confidently design, deploy, and scale enterprise LLM applications using Java.

Profile:

Accomplished Lead Java Full Stack Architect with over 14 years of experience driving innovation in enterprise software engineering, cloud-native systems, and AI-integrated applications. Recognized for original contributions of major significance in designing scalable microservices architectures, secure distributed systems, and high-performance platforms used in mission-critical environments.
Demonstrated expertise in Java, Spring Boot, Microservices, and DevOps, with a strong focus on secure system design and large-scale cloud deployments. Proven ability to architect and lead complex technology solutions that deliver measurable business impact, including performance optimization, cost reduction, and system resilience.
Actively contributes to the global technology community through technical publications, peer review/judging, and innovation in emerging areas such as AI and Large Language Models (LLMs). Holds international patents and published research, reflecting a sustained record of thought leadership and innovation.
Recognized for leadership in cross-functional teams and for advancing engineering excellence through mentorship, architecture governance, and adoption of cutting-edge technologies.