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Metro location and broad skillset increase applicant density despite niche LLM specialization.
Specialized LLM and vector-store skills moderately limit cross-industry transferability.
Many mandatory specialized LLM, Foundry, and vector-store skills required.
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Develop and deploy AI solutions using Microsoft Foundry and agent orchestration frameworks like Semantic Kernel and LangChain.
Design and implement multi-step, tool-calling AI workflows with strong prompt engineering and RAG architecture knowledge.
Collaborate with AI-assisted development tools (GitHub Copilot) and manage AI gateway patterns for multi-provider model routing across cloud AI platforms.
Hands-on experience with Microsoft Foundry for AI solution development and deployment.
Experience with agent orchestration frameworks (Semantic Kernel, LangChain, LangGraph, LlamaIndex).
Proficiency with LLM APIs such as Azure OpenAI, OpenAI, Anthropic, AWS Bedrock.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in building scalable AI workflows involving document ingestion, embeddings, and vector databases (Azure AI Search, Cosmos DB, PostgreSQL).
Strong prompt engineering and knowledge of RAG architectures to improve AI response quality.
Comfortable working in a multi-cloud AI environment managing LLM traffic and integrating with AI assisted development tools.