AI Engineer with .Net/C#

As an AI Engineer, you will bridge cutting-edge AI capabilities with robust enterprise-grade systems. You will design, build, and scale AI-powered solutions using Azure AI services, Azure AI Foundry, and Copilot Studio, integrating them seamlessly into enterprise-grade .NET microservices architectures. Role Specifications: AI & Solution Engineering

• Design and implement AI-driven systems using:
• Azure OpenAI, Azure AI Search, Azure ML
• Azure AI Foundry (agent orchestration, lifecycle)
• Microsoft Copilot Studio (enterprise copilots & workflows)
• Build Retrieval-Augmented Generation (RAG) pipelines:
• Chunking strategies (semantic, recursive, hybrid)
• Embedding and vector search optimization
• Develop multi-agent and conversational AI systems

Application Development (.NET Focus)

• Build and maintain scalable .NET Core microservices
• Develop REST APIs integrating AI services into enterprise platforms
• Ensure high performance, security, and resilience in distributed systems

AI Operations & Optimization

• Deploy and monitor AI systems in production

Optimize:

• Token usage
• Latency and throughput
• Cost efficiency
• Implement observability (logging, telemetry, feedback loops)
• Manage model lifecycle (evaluation, retraining, tuning), Role Overview As a .NET Engineer, you will play a crucial role in shaping the future of AI systems by leveraging your expertise in .NET and C#. Your contributions will directly i…

• 15 days ago

Core Engineering Skills (Mandatory)

• Strong expertise in .NET / C# (microservices architecture)
• Experience building and consuming REST APIs
• Strong understanding of cloud-native architecture (Azure)

AI & Azure Expertise (Mandatory)

• Hands-on experience with:
• Azure OpenAI (prompt engineering, optimization)
• Azure AI Search (vector + hybrid search)
• Azure ML (model lifecycle basics)
• Practical implementation of:
• RAG pipelines
• Embedding strategies
• Retrieval optimization

Copilot & Agentic AI

• Experience with Copilot Studio:
• Conversational agents
• Workflow automation
• Exposure to Azure AI Foundry:
• Agent orchestration
• Multi-agent architecture (preferred for lead/architect