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Experienced AI Engineer specializing in LLM systems and AI application development.
Select and optimize embedding models for semantic search and RAG applications.
Expert in vector databases and semantic search implementation for RAG applications.
Implement advanced API security patterns to protect against common vulnerabilities.
Optimize context windows for AI agents using compaction, masking, caching, and partitioning strategies.
Develop and optimize prompts for AI models efficiently.
Build Retrieval-Augmented Generation (RAG) systems for LLM applications using vector databases and semantic search.
Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns.
Build stateful, multi-actor AI applications with LangGraph, a production-grade framework.
Langfuse is an open-source LLM observability platform for tracing, prompt management, and evaluation of LLM applications.
Reduce AI inference costs effectively and efficiently.
Design and implement multi-agent architectures to enhance task complexity and context management.
Design patterns for building autonomous coding agents, focusing on tool integration and workflows.
Assess the performance of AI systems effectively and efficiently.
Seamlessly integrate LLM capabilities into your application.
Implement comprehensive evaluation strategies for LLM applications using automated metrics and human feedback.
Create and manage AI agent workflows efficiently.
Production-ready patterns for building LLM applications, including RAG pipelines and agent architectures.
AI-driven red team system for identifying vulnerabilities in your infrastructure.
Create robust AI system architectures efficiently.
Structured multi-agent design review to validate and stress-test system designs.
The FAOS Skills Marketplace offers 930+ AI-powered skills and 31 agent plugins for various AI platforms.
Build AI applications using the Azure AI Projects Python SDK for Foundry.
Deploy AI systems seamlessly into production environments.