Description

Key Skills: .NET, C#, ASP.NET Core, Azure OpenAI, LLM Integration, RAG Pipelines, Vector Databases, Semantic Kernel, LangChain, Prompt Engineering

Good to Have Skills: LlamaIndex, AutoGen, ReAct frameworks, Chain-of-Thought techniques, function-calling, Gemini API, OAuth2, JWT authentication, WebSockets, Azure Cognitive Search, Docker containerization, Azure Kubernetes Service, Azure DevOps, Application Insights, monitoring frameworks, and compliance with security and data privacy standards in AI implementations.

Roles & Responsibilities:

• Design and develop scalable backend services and AI integrations using .NET framework and ASP.NET Core.
• Implement tool-calling, memory management, and structured context handling for LLM-driven systems and applications.
• Build and optimize Retrieval-Augmented Generation pipelines using embeddings and vector databases for enhanced search.
• Develop and orchestrate agentic workflows using frameworks such as Semantic Kernel, LangChain, or AutoGen.
• Apply advanced prompt engineering techniques including ReAct, Chain-of-Thought, and function-calling for improved outputs.
• Integrate Azure OpenAI, Gemini, and other LLM APIs into enterprise-grade applications and systems.
• Develop and manage secure APIs using REST, WebSockets, and implement authentication using OAuth2 and JWT.
• Implement caching, logging, monitoring, and performance optimization strategies for AI-powered services and applications.
• Build and deploy cloud-native applications using Microsoft Azure services including App Services and Functions.
• Containerize and deploy applications using Docker and orchestrate using Azure Kubernetes Service where required.
• Develop high-performance and scalable solutions using asynchronous programming, parallel processing, and streaming in .NET.
• Work extensively with embeddings, vector databases, and Azure Cognitive Search for semantic retrieval implementations.
• Ensure secure and efficient communication using web protocols such as HTTP, REST, and WebSockets.
• Implement CI/CD pipelines and DevOps practices using Azure DevOps for continuous integration and deployment.
• Monitor and troubleshoot applications using Azure Monitor, Application Insights, and various logging frameworks.
• Ensure compliance with security, governance, and data privacy standards in AI implementations and deployments.

Experience Required: Experienced professional level with expertise in .NET development, AI integration, and cloud-native application development

Key Skills

Education

Any Graduate