AI Engineer — NATO Secret Clearance, The Hague

EMW; Den Haag; On-site; EUR 70,000 - 110,000; Full time

Job summary

EMW in The Hague, NL is seeking an AI Engineer with NATO SECRET clearance to own end-to-end AI/ML pipelines and secure deployments. You will design, implement, and monitor data-driven AI components, integrating models with scalable backend services in secure environments.

Key duties include building data pipelines, evaluating model performance, and implementing robust observability and lifecycle practices. This role requires strong Python, MLOps, and API development skills in a strict security

Qualifications

• The candidate must have a currently active NATO SECRET security clearance.
• Experience developing, optimising, deploying, and maintaining end-to-end AI/ML pipelines, including training, packaging, monitoring, and lifecycle management.
• Strong hands-on experience in programming, machine learning, software engineering, and applied AI development.
• Solid understanding of machine learning concepts, model evaluation, performance measurement, assessment methods, and model improvement techniques.
• Experience applying pre-trained models, foundation models, LLMs, and Generative AI to practical use cases.
• Experience with RAG, embeddings, vector databases, AI application architectures, and production-grade AI agent backends using LangChain, LlamaIndex, Pydantic AI, or similar.
• Strong experience with MLOps/AIOps, version control, CI/CD, automation, experiment/model lifecycle practices, and build/release workflows.
• Experience developing REST APIs, backend services, and modern Python applications using FastAPI, Pydantic, or similar frameworks.
• Experience with containerisation, orchestration, and deployment technologies including Docker, Kubernetes, Helm, cloud infrastructure provisioning, and workflow orchestration tools such as Airflow or Argo.
• Experience implementing guardrails, observability, logging, monitoring, and operational controls for LLM-based systems.
• Experience working with SQL and NoSQL databases.
• Experience with TypeScript, Node.js, or frontend frameworks such as Next.js.
• Experience working in secure, restricted, or air-gapped environments.

Responsibilities

• Apply machine learning and data science techniques to new problems and datasets, including evaluating model outcomes, performance, and data quality.
• Identify issues in machine learning systems, models, pipelines, datasets, and development activities, and implement practical improvements.
• Design, develop, test, document, amend, refactor, and maintain moderately complex programs, scripts, and AI/ML components.
• Apply agreed engineering standards, tools, and secure development practices to deliver reliable, maintainable, and well-engineered solutions.
• Support AI/software lifecycle engineering by eliciting requirements, selecting suitable working practices, and deploying automation for development, testing, release, deployment, and monitoring.
• Define AI modules for integration builds, produce build definitions, and validate completed modules against agreed functional, quality, security, and performance criteria.
• Build, maintain, and improve data pipelines using data engineering standards and tools, including ETL/ELT processes.
• Monitor progress, report status, communicate risks or blockers, and collaborate with colleagues through reviews and shared delivery ownership.
• Support monitoring of emerging technologies, contribute to technology assessments, reports, roadmaps, and knowledge sharing.

Skills

AI/ML pipelines

Python

LLMs

LangChain

LlamaIndex

Pydantic AI

CI/CD

Docker

Kubernetes

FastAPI

SQL

NoSQL

TypeScript

Node.js

Next.js

Tools

Docker

Kubernetes

Airflow

Argo

FastAPI

Pydantic

LangChain

LlamaIndex

Job description

EMW in The Hague, NL is seeking an AI Engineer with NATO SECRET clearance to own end-to-end AI/ML pipelines and secure deployments. You will design, implement, and monitor data-driven AI components, integrating models with scalable backend services in secure environments.

Key duties include building data pipelines, evaluating model performance, and implementing robust observability and lifecycle practices. This role requires strong Python, MLOps, and API development skills in a strict security