Brij Mohan
LPL Financial
Cary, North Carolina, United States
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Brij Mohan is Vice President - Software Development at LPL Financial, where he leads teams building enterprise-scale AI/ML solutions with a focus on Generative AI and Agentic AI systems. With over 25 years of experience architecting distributed systems in financial technology, he specializes in designing scalable multi-agent architectures that combine the flexibility of microservices with the intelligence of autonomous AI agents.
Brij's expertise spans the full spectrum of modern AI and microservices development, from designing agentic workflows and orchestration patterns to implementing MLOps practices and cloud-native architectures on AWS. His work focuses on practical patterns for agent communication, state management, and coordinating complex AI workflows in enterprise environments.
Brij is passionate about sharing real-world lessons from implementing AI systems at scale and helping developers bridge the gap between agentic AI theory and production-ready solutions.
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From APIs to Autonomous Systems: Building Agentic API Architectures
Modern APIs were designed for human developers and deterministic workflows, but the rise of AI agents is fundamentally changing how APIs are consumed, orchestrated, and governed.
In this session, we explore how APIs are evolving from simple service endpoints into the foundational building blocks of autonomous, multi-agent systems. Drawing from real-world implementations in financial services, we will walk through how agentic architectures leverage APIs as tools for reasoning, decision-making, and execution across complex workflows.
The talk will cover practical patterns for designing APIs that are AI-ready, including self-describing interfaces, dynamic orchestration, and secure tool access using emerging standards such as the Model Context Protocol (MCP). We will also examine how multi-agent systems coordinate across APIs to enable real-time decision-making in areas like financial planning, compliance, and data management.
Attendees will gain actionable insights into:
- Designing APIs for AI agents instead of just human consumers
- Orchestrating multi-agent workflows using API-first architectures
- Balancing autonomy with governance, security, and human oversight
- Lessons learned from deploying agentic systems at enterprise scale
This session is ideal for architects and developers looking to move beyond traditional microservices and toward intelligent, autonomous API ecosystems.
Event-Driven Architectures for Multi-Agent AI Workflows
AI agents are only as powerful as the architecture that supports them. Event-Driven Architecture (EDA) offers a natural fit for multi-agent AI workflows, enabling agents to operate asynchronously, scale independently, and communicate without tight coupling. In this session, we'll explore how to design and build production-ready multi-agent systems using event-driven patterns, walking through real-world examples, live code demonstrations, and architectural blueprints that you can apply immediately.
Building Scalable Multi-Agent Systems: A Microservices Approach
Deploying AI agents in production requires robust microservice architectures. Learn proven patterns for decomposing agents into services, managing inter-agent communication, handling state across distributed systems, and scaling agentic workflows. Includes real-world case studies, code examples, and architectural diagrams for building production-ready multi-agent systems.
PRO WORKSHOP: Building Scalable Multi-Agent Systems: A Microservices Approach
Deploying AI agents in production requires robust microservice architectures. Learn proven patterns for decomposing agents into services, managing inter-agent communication, handling state across distributed systems, and scaling agentic workflows. Includes real-world case studies, code examples, and architectural diagrams for building production-ready multi-agent systems.
Computing and Communication Workshop and Conference
The conference aims to bring together scholars from diverse disciplinary backgrounds to promote the dissemination of ongoing research in Computing and Communication.
The Next Power Shift: Agentic AI in Global Finance
Explored the shift from traditional machine learning to agentic AI in financial services, focusing on how organizations move from prediction to action. The discussion covered key challenges such as balancing probabilistic AI with deterministic financial systems, ensuring auditability and governance, and redefining the role of humans from operators to supervisors. We also examined systemic risks of autonomous agents and where full automation is realistically achievable by 2027.
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