Medline Industries - .Net/AI Engineer

Role Overview : - Design, develop, and maintain enterprise applications using the .NET ecosystem. - Build scalable full-stack applications and APIs using Microsoft technologies. - Integrate AI capabilities into existing and new applications using Azure AI services. - Develop and operationalize AI-powered search, RAG solutions, and assisted/autonomous agents. - Work closely with product, architecture, and business teams to deliver scalable enterprise solutions. Experience : - 7 to 10 years of overall Full Stack development experience. - Strong hands-on experience in the .NET ecosystem. - 2 - 4 years of experience in AI Engineering / Generative AI. - Strong experience with Microsoft Azure technologies. Core Technical Skills - .NET : - Strong expertise in C# and .NET / .NET Core. - Experience developing REST APIs and microservices. - Strong understanding of Object-Oriented Programming and design patterns. - Experience with ASP.NET Core / Web API. - Experience with SQL Server and database development. - Strong understanding of Entity Framework / ORM. - Experience with HTML, CSS, JavaScript/TypeScript. - Exposure to modern frontend frameworks such as React or Angular. - Experience with Azure App Service, Azure DevOps and CI/CD pipelines. - Understanding of Azure cloud architecture, including: 1. Azure App Service 2. Azure Functions 3. Azure Key Vault 4. Azure Monitor 5. Azure Kubernetes Service (AKS) - Experience in application performance tuning, scalability and troubleshooting. - Strong understanding of secure application development and API integration. Must Have : - Hands-on experience with Azure OpenAI Service. - Experience with LLM integration and prompt engineering. - Experience with embeddings and vector-based search. - Strong experience with Azure AI Search, including: Vector Search, Hybrid Search, Reranking. - Experience developing Retrieval-Augmented Generation (RAG) pipelines. - Experience integrating AI capabilities into .NET applications. - Understanding of AI application performance optimization, including: 1. Token optimization 2. Latency optimization 3. Embedding optimization 4. Caching Good to Have : - Experience with Azure Machine Learning. - Experience with Microsoft Power Automate / Power Platform. - Experience with Microsoft Graph API and M365 integration. - Exposure to Microsoft Foundry. - Experience developing AI agents / agentic workflows.