Top Artificial Intelligence Jobs in the Netherlands

Build and ship production AI and software systems across dynamic pricing, procurement, customer automation, content and SEO, demand forecasting, inventory, and internal tooling. The role requires strong commercial judgment, autonomy, hands-on engineering, fluency in LLMs and agentic workflows, and responsibility for measuring business impact. This is a full-time, office-based position in Rotterdam.

Delivers transformation and change consulting engagements, supports proposition development, develops client relationships, contributes to business development, and leads or participates in client projects. The role also develops thought leadership on organizational transformation, digital change, data, and AI. Candidates need relevant consulting experience, strong change and business skills, coaching ability, fluency in Dutch and English, and willingness to travel occasionally.

Support insurance-sector transformation projects through data structuring, data analysis, benchmarking, interviews, workshop facilitation, process mapping, and functional specifications. Consultants will contribute to client delivery, internal knowledge creation, publications, and seminars while developing expertise in data and AI-related opportunities. The role requires strong analytical, problem-solving, communication, teamwork, and entrepreneurial skills, along with excellent English and Dutch.

Leads consulting teams and delivers strategy, business improvement, regulatory risk, innovation, and project management engagements for financial services clients. Responsibilities include selling large programs, mentoring senior consultants, developing client relationships, supporting cross-selling, contributing industry insights, and growing the Dutch market. The role requires extensive management consulting experience, strong banking or insurance connections, business development expertise, and fluency in English and Dutch.

Leads a team of 8–12 QA specialists overseeing GMP quality for commercial manufacturing and supporting digital systems. Partners with Operations, Warehouse, QC, Maintenance, and MSAT; resolves complex compliance issues; improves quality processes; governs ERP, MES, BI, validation, and qualification activities; and supports inspection readiness and regulatory inspections.

Develop and deploy AI and data science solutions for operational teams, translating business needs into production applications. Responsibilities include data collection, cleaning, model evaluation, implementation, API development, cloud automation, and applying technologies such as Azure Cognitive Services, OpenAI, and LLMs. The role also involves presenting solutions, supporting adoption, researching emerging AI technologies, and collaborating in agile teams.

Own end-to-end improvements to Oyster AI, including agent capabilities, tool calling, retrieval, evaluation, infrastructure, and production reliability. Ship LLM-powered features, diagnose failures, manage quality, latency, cost, safety, and access-control trade-offs, and validate improvements through experiments and regression checks. Mentor product teams, establish reusable AI engineering patterns, and collaborate asynchronously across engineering and product.

Own client AI engagements from roadmap and architecture through production and long-term performance. Establish data platform, MLOps, and LLMOps standards; build production-grade AI and agentic systems; mentor engineers; contribute to hiring, account leadership, and engineering practices; and translate technical complexity into decisions for nontechnical stakeholders.

Provides pre-sales technical consulting for industrial automation and autonomy solutions. Advises customers, partners, distributors, and sales teams on control systems, industrial software, cybersecurity, cloud, data, and AI-enabled architectures. Translates customer requirements into solution recommendations, leads demonstrations and proofs of concept, validates technologies, supports modern engineering workflows, and enables ecosystem partners. The role is hybrid in Rotterdam and requires Dutch and English proficiency with travel within the assigned geography.

Develop and productionize customer-facing GenAI applications, including RAG, multi-agent systems, Text2SQL, and fine-tuned models. Advise customers, lead production rollouts, evaluate and optimize AI solutions, communicate technical concepts, collaborate with product and engineering teams, influence the roadmap, and contribute to industry thought leadership. The role requires hands-on data science and machine learning deployment experience across major cloud platforms.

Thesis intern will research how AI can support supply chain process excellence by auditing standardized and meeting-centric workflows. Responsibilities include designing a conceptual process lake, comparing theoretical standards with operational actuals, identifying compliance gaps and improvement opportunities, collaborating with Demand Planning and Process Management stakeholders, and developing actionable recommendations and an implementation roadmap. The internship culminates in an academically rigorous thesis aligned with Mars business objectives.

Design, build, and maintain agentic AI systems for autonomous network optimization. Develop reliable AI/ML pipelines, integrate models into real-time network environments, and establish monitoring, testing, governance, and production ownership practices. Collaborate with network experts, data engineers, software teams, and stakeholders to create scalable solutions using reinforcement learning and emerging AI technologies.

Build and deploy production-grade AI agents and tool-calling workflows on GCP using governed business data. Identify high-value automation opportunities, develop reusable skills, connectors, evaluations, and templates, and establish standards for accuracy, cost, guardrails, and sensitive-data handling. Partner directly with business teams, create runbooks and ownership models, mentor team champions, and demonstrate measurable operational impact through production AI systems.

Design and develop enterprise Java applications using Spring Boot, microservices, cloud platforms, and modern APIs. Drive AI-augmented software delivery by building LLM-, agent-, and RAG-powered solutions. Establish API-first and spec-driven development practices, collaborate with multidisciplinary client teams, mentor engineers, and promote AI-native engineering standards, governance, and productivity tooling.

Freelance AI Specialist responsible for completing and maintaining a shared business knowledge base, improving AI workflows with Claude and Gemini, creating reusable prompts, connecting AI to business tools, documenting processes, training teams, and reporting progress. The role requires careful fact-checking, strong written communication, confidentiality judgment, basic scripting or automation skills, and self-directed project execution.

Supports citywide business improvement and performance management programs through project planning, process analysis, Lean facilitation, training, stakeholder engagement, reporting, and administrative coordination. Manages improvement projects, analyzes workflows and data, develops SOPs, facilitates workshops, prepares dashboards and presentations, and identifies responsible uses of AI and emerging technologies. Requires a bachelor’s degree in a related field and one year of relevant experience.

Leads Vanderlande’s AI and data strategy for Technology, transforming the end-to-end engineering lifecycle through AI-enabled workflows, data products, automation, and reusable engineering capabilities. Owns the portfolio and roadmap, develops the Engineering Configurator, establishes fusion teams, builds organizational AI capability, and ensures responsible AI governance. Success is measured through improved engineering throughput, quality, adoption, reuse, and time to market.

Build and operate Truvio’s shared AI platform for Dynamics 365 products, including LLM routing, retrieval, agent orchestration, evaluations, guardrails, observability, tenant isolation, and developer tooling. Develop reliable infrastructure, SDKs, templates, and documentation that enable product teams to ship AI features safely. Partner with AI leadership and product teams, evaluate models and frameworks, and support compliance, cost management, and production quality measurement.

Build and ship production AI agents for accounts payable, accounts receivable, and treasury workflows using the Truvio AI platform and Dynamics 365. Responsibilities include designing prompts, tools, retrieval, and multi-step workflows; creating evaluation datasets; improving accuracy, cost, and latency; monitoring production quality; investigating failures; and incorporating customer feedback. The role collaborates closely with product managers, consultants, customers, and platform teams to deliver reliable finance automation.

Principal AI Engineer responsible for defining Truvio’s agentic platform architecture and technical direction. The role involves building production AI agents for finance workflows, establishing evaluation, safety, governance, cost, and latency standards, and solving complex reasoning and reliability challenges. The engineer will mentor senior teams, guide model and vendor decisions, influence product strategy, and represent AI technology with customers and partners. Strong hands-on experience with production LLM or agentic systems, distributed systems, and Python or C#/.NET is required.

Lead Oddin.gg’s technology organization and an AI-focused business unit. Partner with the CEO on strategy, priorities, commercial outcomes, and execution. Guide engineering, infrastructure, technical leadership, and data science teams while developing leaders and accountability. Drive practical AI, LLM, and automation capabilities into production, and ensure real-time platforms remain reliable, secure, scalable, and cost-effective.

Develop a generative AI assistant for pricing questions by structuring pricing data and business logic for LLM processing. Analyze large datasets, identify patterns, engage stakeholders to understand business needs, and translate those needs into technical solutions. Collaborate with Pricing and Data Science teams while exploring tools such as Microsoft Copilot and other AI technologies.

Own the AI Gateway product across user onboarding, Gateway credits, provider partnerships, usage-based pricing, enterprise governance, and self-hosted or Cloud deployments. Define model and service offerings, negotiate vendor agreements, shape capabilities such as virtual keys, budgets, policies, reporting, and audit, and lead cross-functional collaboration with engineering, design, sales, finance, security, and enterprise customers.

Own strategic relationships with major cloud, infrastructure, data, and AI platform suppliers. Develop supplier strategies, lead executive governance, support negotiations, challenge pricing and licensing models, optimize technology costs, manage supplier performance and risks, and connect supplier roadmaps with IKEA’s technology priorities. Build internal cloud and platform commercial expertise while collaborating with procurement, architecture, engineering, data, and senior technology stakeholders.

Own end-to-end go-to-market execution, including offer development, positioning, landing pages, paid advertising, outbound campaigns, email sequences, lead generation, experimentation, and funnel analysis. Use AI tools and automation to scale marketing systems, drive sales and business development, improve product-market fit, manage customer relationships, and productize services globally. The role works closely with company co-founders and offers potential equity or revenue participation.