Design LLM-integrated systems at scale and learn how to break them down in FAANG+ interviews.

Break down the architecture behind Uber’s AI assistant for internal knowledge retrieval.

See how embeddings, retrieval, and Slack queries shape real-time backend systems.

Trace how messages are parsed, routed, and evaluated in live production workflows.

Senior ML engineer shares system design insights from Google
-Senior ML Engineer @ Google
-3+ years building multimodal virtual assistants and LLM-based chatbots with focus on safety and security.
-ML Researcher - Ph.D. candidate at University of Waterloo.
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Decode Real Architectures: Learn how Uber’s Genie AI assistant was designed using modern HLD and embedding systems.
Tackle AI Design Interviews: Discover how to break down LLM-powered workflows and answer system design questions.
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Time Zone: Asia/Kolkata
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Discover how top engineers design AI-integrated systems that scale — and crack FAANG+ system design interviews.
Learn how AI agents are embedded into large-scale internal tools like Uber’s Genie.
Understand Slack-style query pipelines and LLM evaluation techniques for reliability.
Get FAANG-level strategies to tackle system design rounds with AI integration.
Discover how top engineers design AI-integrated systems that scale — and crack FAANG+ system design interviews.
Time Zone: Asia/Dhaka
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