Top Artificial Intelligence Jobs in the Netherlands

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 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.

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

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.

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.

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.

Build and ship production AI systems across pricing, procurement, automation, content, and demand prediction. Execute high-leverage LLM and agentic workflow solutions with direct commercial impact, working on-platform in an office-first Rotterdam team.

Author and iterate technical curriculum for experienced engineers transitioning to system architecture: refine syllabus, set measurable learning objectives, produce AI-assisted lessons, design hands-on projects, write rubrics and reviewer guides, and collaborate with LX designers to finalize content over a 4–6 month, part-time engagement (15–20 hrs/week).

Teach and mentor experienced engineers transitioning to system architecture: run live sessions and office hours, review and assess architecture deliverables, run architecture review boards, provide deep technical feedback, record instructional videos, conduct mock interviews, and lead supporting instructors.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLM-driven, iterative agent workflows; deploy high-throughput, low-latency production systems; define evaluation metrics; run experiments and mentor engineers.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLMs over real-time web data, design evaluation metrics, run experiments, deploy high-throughput low-latency systems, and mentor engineers.

Design and prototype AI-powered product experiences from discovery through delivery. Conduct research and usability testing, create wireframes/prototypes, collaborate with product and engineering, maintain design system consistency, and validate solutions to solve real customer problems.

Lead a 4-person Data & AI team to define strategy, prioritize projects, set tech and governance guardrails, and deliver high-impact analytics and AI solutions. Split time between coaching the team and hands-on work (data modelling, capacity forecasting, pricing/AI prototypes), and enable the organisation to adopt AI responsibly and practically.

Join a client-facing squad as a hands-on Senior Full-Stack Engineer working across Kotlin backends and React/TypeScript frontends. Apply AI-native delivery practices and agent/harness engineering to accelerate delivery, unblock the team, and share patterns across the organisation while using AWS and cloud data tooling.

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.

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Design and build research prototypes and production-capable systems to enable portable, interoperable agent and model workflows. Develop model routing, provider abstractions, memory and context representations, benchmarking suites, and evaluation protocols. Run ML experiments, implement robust APIs and integration layers, collaborate across research and engineering, and communicate results via reports, demos, publications, and open-source releases.

Own the AI observability backbone: deploy LLM and agent monitoring with Langfuse; capture traces, latency, token usage, cost, quality scores and safety signals; build Python exporters and tooling; design Grafana dashboards, Prometheus metrics and Azure observability; manage Terraform IaC and CI/CD; instrument workloads for health, cost, and SLA reporting; and support incident investigations.

Hands-on lead full-stack engineer who designs scalable architecture, ships production SaaS features, integrates AI tools, mentors senior engineers, improves deployment pipelines, and drives engineering quality.

Build and own the AI platform that enables fast, safe shipping: prototyping sandbox, CI/CD pipelines, automated tests and evals, agent runtime and orchestration, AI tooling, observability, and reliability. Drive platform standards, quality gates, and production-safe agent workflows so builders can ship rapidly and confidently.

As a Lead AI Engineer, you will lead AI projects, manage teams, and act as a strategic advisor to clients in a consultancy context.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.