Top Artificial Intelligence Jobs in the Netherlands

The Backend Engineer will develop AI Agents, design scalable systems, integrate ML services, optimize performance, and mentor junior engineers.

The AI-First Full-Stack Engineer will lead full-stack development using Node.js and Next.js, integrating AI workflows and orchestrating Claude agent teams for efficient engineering processes, ensuring compliance with healthcare standards.

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

As an AI Product Manager, you will define the product roadmap, collaborate with teams to develop AI features, conduct market research, and ensure ethical AI use.

Seeking an AI/ML Engineer to develop and optimize machine learning models for mobile apps, collaborating with teams to enhance user experiences.

Design and implement agentic tools, translating product needs to production, scale prototypes, improve semantic search, build evaluation pipelines.

Own acquisition, onboarding, and activation for JetBrains AI. Improve product entry points, trials, demos, and onboarding flows. Lead experiments, analyze funnels and cohorts, remove friction, and partner with design, engineering, analytics, marketing, and monetization to drive activation and conversion.

Coordinate and track clinical AI projects across Product, Engineering, Clinical, and Operations. Maintain project plans, trackers, risk logs, and regulatory/compliance documentation (MDR, GDPR). Support planning, reporting, audit readiness, and cross-functional communication to ensure timely, on-scope delivery.

Lead design, training, and evaluation of LLMs for translation and language-quality tasks; build robust evaluation frameworks; architect agentic multi-model workflows; own model development from data curation to production; run reproducible experiments; collaborate with product and engineering and mentor researchers.

Lead research and analysis of the enterprise AI services market, build market-sizing and forecasting models, publish thought leadership, advise C-level clients, present at events, support sales and peer review, mentor junior analysts, and drive research process improvements to deliver actionable insights on AI services and competitive dynamics.

The Site Reliability Engineer ensures user-facing services run smoothly, focuses on systems reliability and scalability, and enhances operational practices through automation and engineering principles.

Own the AI platform roadmap and build reusable capabilities (prompting, RAG, tool calling, agents, evaluation, observability). Run discovery, prioritize AI investments, partner with Product, Engineering, Design and Data, guide other PMs, define success metrics, and ensure scalable, reliable AI-powered features that deliver customer and business value.

Design, build, and maintain production-grade AI services and APIs using LLMs and custom models. Develop agentic orchestration, semantic retrieval, and vector-search systems. Implement scalable Python microservices, shared libraries, observability, and CI/CD. Collaborate across product and platform teams, conduct performance tuning, and mentor engineers throughout the full software lifecycle.

Lead design and delivery of AI-powered features for CLion and C++ workflows. Architect AI integrations and agent tools, prototype and validate debugging, code-understanding, refactoring, and navigation workflows, build benchmarks and evaluation frameworks, and collaborate with product, ML, QA, and engineering teams to set technical direction and roadmap for AI-assisted C++ development.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

Own the end-to-end process converting product, marketing, and account signals into qualified sales opportunities. Build qualification criteria, routing rules, data enrichment and automation, partner across product/marketing/sales/analytics, create feedback loops, and measure and optimize funnel conversion and data quality.

The Applied AI Engineer will support customer adoption of AI products, integrate AI models into applications, and improve product capabilities based on feedback.

Design, build, and maintain scalable cloud infrastructure and APIs on GCP to support AI applications and robotic integrations. Collaborate with ML and web teams, optimize cost/performance, implement IaC and containerized services, and participate in testing and reliability work.

Define architectural direction, guardrails and reusable patterns for secure, compliant, scalable AI and workflow automation. Advise stakeholders, lead DevOps practices, mentor teams, and provide guidance to project teams and citizen developers across the region.

Work within the Creative Studio/Technology team to design and build AI agents and image-processing pipelines. Prototype and integrate generative AI and computer-vision models into production workflows, develop tooling, and deliver tasks from brief to deployment while collaborating with designers and creatives.

As a Staff/Senior AI Engineer, you will develop production-ready coding agents and improve AI model capabilities for JetBrains' software development tools. Collaborating with teams, you'll focus on model training, evaluation, and product integration to enhance user experience.

As a Senior Software Engineer, you will design and implement AI-powered agents to automate assurance workflows and build production-ready solutions. You'll collaborate with product teams to enhance the development process and maintain high standards in code quality and architecture.

The Senior Full Stack Engineer will develop the GenAI platform, design full-stack applications, ensure secure coding practices, and collaborate with teams to enhance AI agents in pivotal industries.

Evaluate Gemini personalization by designing multi-turn prompts based on personal context, scoring responses for relevance, personalization, hallucinations and grounding, validating data usage, ranking outputs, writing rationales, and maintaining data hygiene while collaborating with remote teams.

Lead strategic AI and experience orchestration engagements with account teams to accelerate adoption of Genesys AI capabilities. Shape AI use cases, lead workshops, influence deal strategy, support proposals/pricing, and drive sales enablement and field execution across the AI portfolio to deliver measurable customer outcomes.