Azure AI Foundry Engineer — GenAI & LLM Solutions

MPower Plus; Zaandam; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

MPower Plus is seeking an experienced AI/GenAI engineer to design, develop, and deploy enterprise-grade solutions on the Microsoft Azure AI Foundry platform in Zaandam. You will work in a hybrid setup, collaborating with architects, data teams, and stakeholders to translate business needs into scalable AI workflows.

You should be proficient with LLMs, embeddings, vector databases, Python, and REST APIs, and you will own governance, security, and monitoring across AI pipelines.

Qualifications

• Hands-on experience with Azure AI Foundry / Azure AI ecosystem (OpenAI, ML, Cognitive Services).
• Strong knowledge of LLMs, Prompt Engineering, RAG, and Agent-based architecture.
• Proficiency in Python / REST APIs / SDK-based development.
• Understanding of AI lifecycle (design, deployment, integration, monitoring).
• Experience with embeddings, vector DB/search, and data pipelines.
• Knowledge of AI governance, security, and compliance.

Responsibilities

• Design and implement AI/GenAI solutions using Azure AI Foundry (agentic AI, pipelines, orchestration).
• Build and integrate LLM-based applications using Azure OpenAI, AI Search, and Cognitive Services.
• Develop AI agents, workflows, and automation solutions using Foundry SDKs and services.
• Implement Retrieval-Augmented Generation (RAG) and vector search solutions.
• Ensure governance, security, compliance, and responsible AI practices.
• Monitor, evaluate, and optimize AI models and pipelines.
• Collaborate with stakeholders, architects, and data teams to deliver AI solutions.

Skills

Azure AI Foundry

LLMs

Prompt Engineering

Agent-based architecture

Python

REST APIs

SDK-based development

RAG

Vector embeddings

AI governance

Tools

Azure OpenAI

Foundry SDKs

Vector DBs

Job description

MPower Plus is seeking an experienced AI/GenAI engineer to design, develop, and deploy enterprise-grade solutions on the Microsoft Azure AI Foundry platform in Zaandam. You will work in a hybrid setup, collaborating with architects, data teams, and stakeholders to translate business needs into scalable AI workflows.

You should be proficient with LLMs, embeddings, vector databases, Python, and REST APIs, and you will own governance, security, and monitoring across AI pipelines.