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Role Description

We are seeking an experienced AI Application Developer with strong .NET and Azure AI expertise to support enterprise initiatives focused on modernizing operational systems through artificial intelligence. This role involves designing and implementing AI-powered enterprise applications that enhance digital services, automate workflows, and improve operational efficiency.

• Build AI-enabled web applications using ASP.NET Core, Azure AI Services, and modern AI orchestration frameworks.
• Integrate enterprise systems with large language models (LLMs) deployed in both cloud and local environments.
• Collaborate closely with AI engineers, data scientists, DevOps teams, and enterprise application developers within an agile development environment.

Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience.
• 3+ years of experience developing applications using ASP.NET Core or ASP.NET MVC.
• Strong development experience using C# and RESTful APIs.
• Experience integrating applications with Azure AI services such as Azure OpenAI, Azure Cognitive Services, and Azure Cognitive Search.
• Experience running or integrating locally hosted large language models using tools such as Ollama.
• Hands-on experience with AI orchestration frameworks such as Semantic Kernel or AutoGen.
• Strong knowledge of AI architecture patterns including Retrieval-Augmented Generation (RAG), vector search, and semantic search.
• Experience with asynchronous programming and scalable service architectures.
• Familiarity with Azure Blob Storage, Azure Functions, and Azure DevOps CI/CD pipelines.

Requirements

• Integrate enterprise applications with Azure AI services, including Azure OpenAI, Cognitive Services, and Cognitive Search.
• Design hybrid AI architectures that support both cloud-hosted and locally deployed LLMs.
• Implement Retrieval-Augmented Generation (RAG) pipelines to enable contextual AI responses.
• Develop vector search and semantic search capabilities using embeddings and vector databases.
• Build systems enabling contextual retrieval of enterprise knowledge and operational data.
• Develop intelligent agent orchestration frameworks for complex AI workflows.
• Implement multi-agent systems using frameworks such as Semantic Kernel or AutoGen.
• Design automation systems capable of multi-step reasoning and task execution.
• Implement Model Context Protocol (MCP) or similar interoperability frameworks for AI agents and enterprise services.
• Create AI-driven automation to enhance operational processes and digital service delivery.
• Optimize AI application performance, latency, and operational costs.
• Manage hybrid inference environments including both cloud-based and locally hosted LLMs.
• Develop scalable deployment strategies for enterprise AI systems.
• Collaborate with DevOps teams to integrate AI workloads into CI/CD pipelines.
• Participate in Agile development cycles, typically operating in three-week sprint iterations.
• Provide weekly development updates and technical documentation.
• Communicate project progress, risks, and blockers to technical leadership.
• Deliver production-ready code and maintain documentation for enterprise AI solutions.

Benefits

• Experience building AI copilots or enterprise virtual assistants.
• Development of LLM-powered chat interfaces and conversational AI solutions.
• Experience building multi-agent AI systems.
• Knowledge of embedding generation and vector indexing techniques.
• Experience implementing hybrid retrieval strategies for enterprise data.
• Familiarity with Model Context Protocol (MCP) or similar interoperability frameworks.
• Experience with LangChain or ML.NET frameworks.
• Experience implementing OpenAI function calling or tool integration frameworks.
• Experience deploying AI models in both cloud and local inference environments.
• Experience working in enterprise or government technology environments.
• Familiarity with WCAG accessibility standards.