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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Azure AI Engineer Retrieval Augmented Generation (RAG) - **Company:** CareerCircle - **Location:** Milwaukee, WI, United States - **Salary:** $135,200.0 - $176,800.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Microsoft Azure, Python (Programming Language), Knowledge Management, Machine Learning, Metadata, Language Modeling, Performance Tuning, Search Technologies, Software Engineering, Systems Integration, Data Ingestion, Large Language Models, Prompt Engineering, IT Architecture, Model Validation, Generative AI, Indexer, Virtual Agents - **Published:** September 26, 2026 - **Apply:** https://www.careercircle.com/jobs/all/all/usa/wi/milwaukee/cad40b0c-a091-4484-9711-2b7cd6ac0711 ## About the Role * Hands-on experience with Azure AI Foundry, including building and refining AI applications within the Azure ecosystem. * Practical experience building, tuning, or optimizing Retrieval Augmented Generation (RAG) solutions in production or near-production environments. * Experience with Vibe Coding and the ability to apply it in the context of Azure AI and RAG pipelines. * Strong understanding of document ingestion processes, including chunking strategies, metadata tagging, indexing, ranking, and reranking. * Proven experience improving search relevance and retrieval accuracy within AI-driven applications. * Knowledge of vector search, semantic search, and retrieval optimization concepts and how to apply them in Azure-based solutions. * Experience testing and validating prompt strategies and AI response quality, including iterative prompt engineering and evaluation. * Ability to work independently within an established environment and deliver incremental enhancements without extensive supervision. * mid-level Azure AI Engineer, Applied AI Engineer, Machine Learning Engineer, Search/Relevance Engineer, or Software Engineer with direct experience building and tuning RAG solutions in Azure., * Experience supporting customer service or knowledge management AI solutions, particularly those used by product support or help desk organizations. * Experience with Azure Cognitive Search or Azure AI Search and integrating these services into RAG architectures. * Familiarity with large language model (LLM) evaluation frameworks and methods for testing response quality and robustness. * Experience working with technical documentation, manuals, and product support content to design effective retrieval and search strategies. * Comfort collaborating with both business stakeholders and technical teams to translate requirements into concrete AI enhancements., Individual compensation offered for this position within this range will depend on many factors, including qualifications, skills, relevant experience, job knowledge, geographic location, internal equity, and other pertinent job-related factors. ## Description Indexing Chunking Visionary Innovation Vibe Coding Microsoft Azure Product Support Semantic Search Customer Service Customer Support Machine Learning Help Desk Support Inventory Staging Prompt Engineering Search Technologies Software Engineering Knowledge Management Artificial Intelligence Technical Documentation Large Language Modeling Search Engine Optimization Engineering Design Process Retrieval Augmented Generation Large Language Model Evaluation Applications Of Artificial Intelligence, We are seeking a hands-on Azure AI Engineer to optimize and enhance an existing Retrieval Augmented Generation (RAG) application built within the Microsoft Azure AI ecosystem. The core architecture and infrastructure are already in place and are approximately 80% functional. Your primary goal will be to improve retrieval accuracy, response quality, and overall performance for a customer-facing knowledge application used by a product support organization. This is a technical execution role focused on building, tuning, and refining RAG solutions, rather than AI architecture or strategy., * Optimize and refine an existing RAG implementation built in Azure AI Foundry to improve performance and reliability. * Improve retrieval accuracy, ranking, reranking, and context selection to deliver more relevant responses for customer-facing use cases. * Configure and enhance document ingestion pipelines, including chunking strategies, metadata tagging, indexing approaches, and search optimization techniques. * Evaluate and tune development and staging environments to improve response quality and system performance. * Work with large document sets such as manuals, specifications, and technical documentation to improve retrieval effectiveness and coverage. * Enhance prompt engineering techniques and context window strategies to increase first-response accuracy and reduce the need for follow-up queries. * Collaborate with business and technical teams to understand requirements and implement a backlog of planned enhancements and improvements. * Test and validate retrieval and response quality using real-world customer support scenarios and knowledge application use cases. * Continuously monitor, analyze, and iterate on RAG pipeline performance to ensure ongoing optimization of search relevance and response quality., Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools. Related Jobs Azure AI Engineer (RAG Optimization) Actalent Milwaukee, WI | Milwaukee, WI*On-Site | On-Site Metadata Indexing Chunking Visionary Innovation Vibe Coding Microsoft Azure Product Support Semantic Search Customer Service Customer Support Machine Learning Help Desk Support Inventory Staging Prompt Engineering Search Technologies Software Engineering Knowledge Management Artificial Intelligence Technical Documentation Large Language Modeling Search Engine Optimization Engineering Design Process Retrieval Augmented Generation Large Language Model Evaluation Applications Of Artificial Intelligence +0 Google IT Automation with Python Google IT Automation with Python