.NET AI/ML Developer (Generative AI)

Project Overview 

The project involves creating an intelligent chatbot that enables users to query a complex knowledge base (intranet pages, posts, PDFs, etc.). The technical challenge is building a high-performance AI service within the existing .NET ecosystem. The solution must handle sophisticated multi-tenant access control, ensuring the AI generates answers strictly based on the user's dynamic access rights. 

Technical Approach 

• AI Service: Developed as a standalone microservice using .NET 8/9 and C#. 
• Integration: Seamless communication with the existing .NET/Angular platform via REST API. 
• AI Frameworks: Utilization of Microsoft Semantic Kernel or similar .NET-native AI orchestration tools. 

• Core Logic: Implementation of RAG (Retrieval-Augmented Generation) pipelines and vector search within the .NET stack. 

   

Duties and Responsibilities 

• Design and implementation of a .NET-based AI microservice utilizing OpenAI models. 
• Development of RAG pipelines in C# to process and retrieve information from various document formats. 
• Implementation of Tenant-Aware AI logic to mirror the platform’s dynamic role-based access structure. 
• Ensuring high response quality with mandatory Source Attribution (links to original documents). 
• Applying technical guardrails to minimize hallucinations and ensure factual accuracy. 
• Deploying and managing the microservice within a Dockerized environment. 
• Collaborating with the core .NET team to define a scalable integration and data synchronization strategy. 

• Creating technical documentation for the internal development team. 

   

Skills and Qualifications 

• B.Sc. or M.Sc. degree in computer science, applied math, or similar. 
• 7+ years of experience in .NET development (C#), with a strong focus on backend architecture. 
• 2+ years of experience working with Generative AI, LLMs, and OpenAI APIs within the .NET ecosystem. 
• Proficiency in Microsoft Semantic Kernel, AutoGen, or LangChain.net. 
• Solid understanding of vector databases (e.g., Pinecone, Weaviate, or pgvector) and RAG techniques. 
• Experience with Docker and cloud-native deployment (AWS, UpCloud, or Azure). 
• B2+ English communication skills. 
• High responsibility, pro-activity, and attention to technical details.