You’ll work across backend, AI orchestration, and lightweight frontend layers to deliver scalable, observable, and reliable AI systems. Your focus will be on agent-based architectures , LLM integrations , and automation flows , rather than traditional CRUD applications.

You’ll have significant autonomy in technical decisions, influence architectural direction, and help define best practices for building AI systems that are ready for real-world production use.

Key Responsibilities

• Design and build end-to-end AI applications that leverage LLMs for reasoning, automation, and decision-making.
• Implement agentic architectures using frameworks such as LangChain, LlamaIndex, and PydanticAI .
• Develop backend services and orchestration layers in Python and Go , with supporting components in TypeScript where needed.
• Build and maintain LLM-powered workflows that integrate with internal systems, APIs, and external tools.
• Apply strong prompt engineering practices to ensure reliability, safety, and predictable model behavior.
• Work hands-on with LLM models , embeddings, retrieval (RAG), and tool calling.
• Implement LLM observability using tools like Langfuse , including tracing, evaluation, and cost monitoring.
• Ensure AI systems are scalable, testable, and production-ready .
• Collaborate with platform, product, and security teams to align AI capabilities with infrastructure and compliance requirements.
• Take ownership of AI system architecture and continuously evolve it as usage and complexity grow.

What Your Day Will Not Look Like

• Building mostly static UIs or traditional frontend-heavy applications.
• Writing experimental AI demos without production considerations.
• Working on isolated scripts with no architectural or system-level impact.

What You Bring

• Strong experience as a full-stack or backend engineer with a clear focus on AI-driven systems.
• Hands-on expertise with Python , plus working knowledge of Go and TypeScript .
• Proven experience building applications that integrate with LLMs in production environments.
• Solid understanding of agent-based systems , workflow orchestration, and AI system design.
• Practical experience with prompt engineering , model selection, and LLM evaluation.
• Familiarity with LLM observability concepts: tracing, monitoring, feedback loops, and cost control.
• An ownership mindset and the ability to design systems that scale beyond prototypes.

Bonus Points If You Have

• Experience deploying AI systems on cloud-native or Kubernetes-based platforms.
• Familiarity with RAG pipelines, vector databases, or embedding strategies.
• Experience designing developer-facing AI platforms or internal AI tooling.
• Interest in reliability, safety, and governance of AI systems.
• Experience mentoring engineers or acting as a technical lead.

Eligibility & Application Information

We welcome non-native Dutch speakers to apply. However, to be eligible, you must:

• Have a valid work permit in the Netherlands.
• Reside in the Netherlands and be able to travel to the office near The Hague.
• Be fluent in English (Dutch is not required).

Ready to build production-grade AI systems that go beyond demos?

Apply now through Frank Poll and help Nebul shape the future of intelligent, sovereign AI applications.