GenAI engineer for agentic AI applications

NDA; Amsterdam; On-site; EUR 90,000 - 150,000; Full time

Job summary

NDA in Amsterdam, Netherlands, is seeking GenAI engineers to join its Intelligent Automation team. You will design, build and deploy production-grade GenAI and Agentic AI applications, and develop AI agents and workflows using n8n, Langflow, or LangGraph.

Build RAG solutions with vector databases and embeddings, develop scalable backend services in Python and FastAPI, and integrate AI with MCPs and AWS. Strong emphasis on observability and end-to-end production delivery.

Qualifications

• Proven experience delivering GenAI products into production.
• Hands-on with AI orchestration tools and AI workflows.
• Strong Python, FastAPI and AWS background.
• Experience with vector databases and retrieval techniques.

Responsibilities

• Design, build, and deploy production-grade GenAI and Agentic AI applications.
• Develop AI agents and workflows using n8n, Langflow, LangGraph.
• Build RAG solutions using vector databases, embeddings, and retrieval.
• Develop scalable backend services using Python and FastAPI.
• Integrate AI applications with MCPs and AWS cloud infrastructure.
• Implement AI evaluations, monitoring, and performance optimisation.
• Deliver end-to-end GenAI products into production (2–3 live apps desirable).

Skills

GenAI expertise

Agentic AI

AI product delivery

End-to-end delivery

Observability

Tools

n8n

Langflow

LangGraph

Python

FastAPI

AWS

Docker

Kubernetes

CI/CD

React

Next.js

TypeScript

ML tooling

Vector databases

Embeddings

MCP integrations

Job description

GenAI engineer for agentic AI applications

A global technology organisation is seeking GenAI and Agentic AI Engineers for its Intelligent Automation team.

• Design, build, and deploy production-grade GenAI and Agentic AI applications
• Develop AI agents and workflows using n8n, Langflow, LangGraph, or similar frameworks
• Build RAG solutions using vector databases, embeddings, and retrieval techniques
• Develop scalable backend services using Python and FastAPI
• Integrate AI applications with MCPs and AWS cloud infrastructure
• Implement AI evaluations, monitoring, and performance optimisation
• Proven experience delivering end-to-end GenAI products into production, ideally 2–3 live applications
• Hands-on experience with AI orchestration tools such as n8n, Langflow, or LangGraph
• Strong knowledge of RAG, embeddings, and vector databases
• Proficiency in Python, FastAPI, and AWS (S3, EC2, RDS)
• Experience with MCP integrations and AI deployment
• Experience with React, Next.js, and TypeScript
• Experience with Docker, Kubernetes, and CI/CD
• Knowledge of LLM fine-tuning, evaluations, and observability
• Experience with Claude Code, Cursor, or Codex