C005309 AI Engineer (NS) - THU 24 Sep

Deadline Date: Thursday 24 September 2026 Requirement: AI Engineer Location: The Hague, NL Full Time On-Site: Yes Time On-Site: 100% Total Scope of the request (hours): 278 Required Start Date: 30 October 2026 End Contract Date: 31 December 2026 Required Security Clearance: NATO SECRET Duties & Role: • 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. Requirements Skills, Knowledge & Experience: • 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 frameworks such as 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.