AI Agent Engineer: Building Production-Ready Multi-Agent Systems (SF)
About This Course
This advanced 5-day training program enables developers and architects to build intelligent, autonomous multi-agent systems using modular tools for agent definition, orchestration, and memory-driven task resolution. Participants move beyond traditional retrieval methods to designing structured and scalable agentic workflows that interact with multiple knowledge sources—files, APIs, and databases—before reasoning and responding.
The program culminates in designing and deploying an MCP (Model Context Protocol) Server, a context manager that governs how agents fetch, evaluate, rank, and synthesize information from different sources in sequence or parallel. This capability mimics human-like reasoning and is applicable in decision-heavy enterprise applications.
What You'll Learn
LO1 Implement Retrieval Augmented Generation (RAG) by applying context augmentation concepts through the use of vector databases and retrieval algorithms
LO2 Maintain Generative AI development environments by configuring software settings and developer frameworks to ensure optimal application performance and stability.
LO3 Troubleshoot AI systems to identify performance issues using systematic software procedures.
LO4 Document potential technical issues with AI application tools and escalate them to relevant stakeholders.
LO5 Integrate AI models and prompt engineering into application by using no-code, low code development application.
Entry Requirements
• The candidate should hold a diploma and have at least 2 years of experience working as a developer/programmer.
• Candidates who do not meet the above requirements will be assessed on case to case basis.