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About the role
Role Overview: You will be an AI Engineer responsible for building, evaluating, and operating LLM-powered agents and workflows using Microsoft AI Foundry and Azure AI services. Your role will involve combining deep Python development with prompt engineering, agent orchestration, and AI evaluation to deliver reliable supply chain AI solutions. Key Responsibilities: - Develop AI agents for supply chain planning, forecasting, exception handling, and decision support. - Implement agent orchestration logic including task routing, tool invocation, and memory management. - Build RAG pipelines using Azure AI Search, vector embeddings, and enterprise data sources. - Design and optimize prompts and system instructions for accuracy and consistency. - Implement automated evaluation pipelines: - Prompt and response evaluation - Regression testing for agent behavior - Cost and latency monitoring - Apply guardrails and safety mechanisms such as policy enforcement and output validation. - Integrate AI services into APIs and applications. - Collaborate with data engineers to ensure data quality and relevance. Qualifications Required: - Strong Python engineering skills. - Hands-on experience with LLMs and agent frameworks. - Solid understanding of prompt engineering, embeddings, and vector search. - Experience deploying AI solutions on Azure. - Experience with AI evaluation, testing, and monitoring. Additional Details: The nice-to-have skills include: - Full-stack development experience. - Familiarity with Responsible AI practices. - Supply chain AI or analytics experience. Role Overview: You will be an AI Engineer responsible for building, evaluating, and operating LLM-powered agents and workflows using Microsoft AI Foundry and Azure AI services. Your role will involve combining deep Python development with prompt engineering, agent orchestration, and AI evaluation to deliver reliable supply chain AI solutions. Key Responsibilities: - Develop AI agents for supply chain planning, forecasting, exception handling, and decision support. - Implement agent orchestration logic including task routing, tool invocation, and memory management. - Build RAG pipelines using Azure AI Search, vector embeddings, and enterprise data sources. - Design and optimize prompts and system instructions for accuracy and consistency. - Implement automated evaluation pipelines: - Prompt and response evaluation - Regression testing for agent behavior - Cost and latency monitoring - Apply guardrails and safety mechanisms such as policy enforcement and output validation. - Integrate AI services into APIs and applications. - Collaborate with data engineers to ensure data quality and relevance. Qualifications Required: - Strong Python engineering skills. - Hands-on experience with LLMs and agent frameworks. - Solid understanding of prompt engineering, embeddings, and vector search. - Experience deploying AI solutions on Azure. - Experience with AI evaluation, testing, and monitoring. Additional Details: The nice-to-have skills include: - Full-stack development experience. - Familiarity with Responsible AI practices. - Supply chain AI or analytics experience.
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