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# AI Engineer

- **Company:** Spektrum
- **Location:** Den Haag, Netherlands
- **Contract:** Contract
- **Skills:** Artificial Intelligence, Airflow, Cloud Computing, Continuous Integration, Extract Transform Load (ETL), Machine Learning, Node.Js, NoSQL, Next.js, Secure Coding, Software Engineering, SQL Databases, TypeScript, Workflow Management Systems, Large Language Models, Model Validation, Generative AI, Backend, Fastapi, Kubernetes, Machine Learning Operations, Virtual Agents, Restful APIs, Code Restructuring, Software Version Control, Data Pipelines, Docker
- **Published:** September 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ba2c36a06e1f4d97

## About the Role

* Experience developing, optimising, deploying, and maintaining end-to-end AI/ML pipelines (training, packaging, monitoring, lifecycle management)
 * Strong hands-on programming, machine learning, and applied AI development experience
 * Solid understanding of ML concepts, model evaluation, and performance measurement
 * Experience applying pre-trained/foundation models, LLMs, and Generative AI to practical use cases
 * Experience with RAG, embeddings, vector databases, and production-grade AI agent backends (LangChain, LlamaIndex, Pydantic AI, or similar)
 * Strong MLOps/AIOps experience: version control, CI/CD, automation, build/release workflows
 * Experience developing REST APIs and backend services (FastAPI, Pydantic, or similar)
 * Experience with Docker, Kubernetes, Helm, cloud infrastructure, and orchestration tools (Airflow, Argo)
 * Experience implementing guardrails, observability, and monitoring for LLM-based systems
 * Experience with SQL and NoSQL databases
 * Experience with TypeScript, Node.js, or Next.js (nice to have)
 * Experience working in secure, restricted, or air-gapped environments

## Description

NATO NCIA AI Engineer to design, build, and maintain AI/ML components and pipelines supporting mission-critical systems. This role sits at the intersection of applied machine learning, software engineering, and MLOps, covering everything from model evaluation and data pipeline development to production-grade LLM/AI agent deployment. The successful candidate will work within secure, structured engineering practices to deliver reliable, well-documented, and maintainable AI solutions., * Identify issues in ML systems, models, pipelines, and datasets, implementing practical improvements

 * Design, develop, test, document, refactor, and maintain moderately complex programs, scripts, and AI/ML components
 * Apply agreed engineering standards, tools, and secure development practices
 * Support AI/software lifecycle engineering, including requirements elicitation and automation for development, testing, release, deployment, and monitoring
 * Define AI modules for integration builds and validate against functional, quality, security, and performance criteria
 * Build, maintain, and improve data pipelines using ETL/ELT processes
 * Monitor progress, report status, and communicate risks or blockers
 * Contribute to technology assessments, roadmaps, and knowledge sharing


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