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AI Engineer

Sqli — Netherlands · Posted ~1 hour ago

Full-time

Skills

C# .NET Azure Azure AI Foundry Azure OpenAI Semantic Kernel Microsoft Agent Framework RAG LLM Orchestration AI Agents APIs Event-Driven Architecture Azure AI Search Embeddings Vector Stores LLMs

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Summary ✨ AI‑Generated

Design, build, and operate enterprise AI applications within a major cloud ecosystem. You will develop agents, RAG pipelines, and LLM-powered integrations using C#/.NET, connect AI capabilities to APIs and event-driven services, and build retrieval and knowledge layers using search, embeddings, and vector technologies.

Highlights

Build production-grade AI applications and agents on Azure, combining modern generative AI patterns with strong .NET engineering practices and direct collaboration with enterprise client teams.

Description

Descripción del empleoWe are looking for an AI Engineer with a strong Microsoft technology background. He/She will play a key role in designing, building and operating AI-powered applications within the Azure ecosystem, working side by side with client teams to bring enterprise AI use cases from concept to production. He/She will combine solid .NET engineering practices with modern AI application patterns (agents, RAG, LLM orchestration) to deliver solutions that client teams can understand, operate and evolve. What is this all about? * Design and build AI-powered applications and agents on the Azure AI stack (Azure AI Foundry, Azure OpenAI) * Develop agent orchestration, RAG pipelines and tool/function calling in C#/.NET using Semantic Kernel or Microsoft Agent Framework * Integrate LLM capabilities into enterprise applications and services (APIs, event-driven architectures) * Build and maintain knowledge bases and retrieval layers with Azure AI Search, embeddings and vector stores * Implement evaluation of AI outputs (test datasets, quality metrics, prompt iteration) so solutions are measurable, not just plausible * Apply enterprise-grade security, identity (Microsoft Entra ID), networking and observability practices to AI workloads * Automate build, deployment and analysis workflows with Azure DevOps pipelines * Work embedded with client technical teams in an Agile / Scrum environment * Present progress, solutions and recommendations to international stakeholders in English * Document architectures, patterns and decisions, and propose continuous improvement