GenAI Platform Engineer (medior)

Details

• Title: GenAI Platform Engineer (medior)
• Start date: ASAP
• End date: 31‑12‑2026 (option to extend)
• Location / Hybrid: Den Bosch (fixed office days Tuesday & Wednesday)
• Hours: 32–40 per week
• Languages: English & Dutch (both possible)

About

Expert in making Generative AI accessible and reliable for the organization, enabling colleagues to move quickly from idea to working AI solution. The GenAI Platform Engineer will develop a robust and scalable AI platform that is essential for the organization to start using Generative AI responsibly and efficiently. The role combines technical execution—cloud infrastructure, GenAI, and platform development for reusable components—with advising and guiding teams on their AI journey.

Responsibilities

• Develop and maintain AWS cloud infrastructure using technologies such as Lambda, ECS, Bedrock, and CDK.
• Build reusable building blocks for Retrieval‑Augmented Generation (RAG) pipelines, agentic workflows, and AI Gateway integrations.
• Set up and support databases (PostgreSQL, vector databases, NoSQL) required for GenAI use cases.
• Implement AI observability with tools like Langfuse, Langsmith, and evaluation frameworks.
• Develop with Python and TypeScript for both backend services and frontend integrations.
• Advise teams, conduct workshops, and transfer knowledge on GenAI best practices and implementations.

Technical Requirements

• Minimum 5 years of experience as a Platform Engineer, DevOps Engineer, Cloud Engineer, or AI Engineer.
• At least 1 year of demonstrable experience implementing Generative AI technologies (LLMs, RAG, agentic workflows).
• Strong knowledge of AWS cloud services (Lambda, ECS, Bedrock).
• Experience with Infrastructure as Code (CDK, Terraform, or similar).
• Proficiency in Python and working knowledge of TypeScript.
• Experience with various databases in Generative AI projects (SQL, NoSQL, vector databases, graph databases).
• Knowledge of AI observability tools (Langfuse, MLflow, or similar).
• Familiarity with Model Context Protocol (MCP).
• Curiosity and passion for knowledge sharing.
• Ability to translate complex technical concepts into understandable solutions.