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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.
The ideal candidate will build AI-enabled web applications using ASP.NET Core, Azure AI Services, and modern AI orchestration frameworks, integrating enterprise systems with large language models (LLMs) deployed in both cloud and local environments. The developer will collaborate closely with AI engineers, data scientists, DevOps teams, and enterprise application developers within an agile development environment.
Design, develop, and maintain AI-powered enterprise applications using ASP.NET Core and C#.
Build intelligent solutions such as virtual assistants, chat interfaces, and operational automation tools.
Develop RESTful APIs and backend services that integrate enterprise systems with AI models.
Implement AI capabilities within existing enterprise applications.
Architect secure, scalable systems that support enterprise AI functionality.
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.
Collaborate with AI engineers, data scientists, DevOps engineers, and enterprise developers.
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.
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
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
Semantic search
Experience with asynchronous programming and scalable service architectures.
Familiarity with Azure Blob Storage, Azure Functions, and Azure DevOps CI/CD pipelines.
Candidates with the following experience will be highly preferred:
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.
Semantic Kernel
AutoGen
LangChain
Large Language Models (LLMs)
Retrieval-Augmented Generation (RAG)
Vector Search
Semantic Search
AI Agents
Microsoft Azure
Azure AI Services
Azure OpenAI
Azure Cognitive Search
Ollama
Local LLM inference
Hybrid cloud AI architectures
Azure DevOps
CI/CD pipelines
Cloud deployment automation
Agile development environment with sprint-based delivery cycles.
Collaboration with AI engineers, DevOps teams, and enterprise application developers.
Weekly progress reporting and technical documentation requirements.
Enterprise technology environment focused on modernizing digital services through AI innovation
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