Top Artificial Intelligence Jobs in the Netherlands

Join Welo Data’s remote Hausa AI contributor network for future projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural accuracy review. This is not an active opening; selected contributors will receive project details, timelines, and compensation when suitable work becomes available.

Join a remote contributor network supporting AI training projects through text, image, and audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before each assignment. Native or near-native Kazakh fluency, English proficiency, digital tool comfort, and strong attention to detail are required.

Join Welo Data’s remote Afrikaans contributor network to support AI training projects through text, image, or audio annotation; search, advertising, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. Projects vary from several days to weeks, with compensation and timelines provided before each assignment. This is a talent-community application rather than an active job opening.

Join Welo Data’s remote Yoruba AI contributor network based in Nigeria. Projects may involve annotating text, images, or audio; evaluating search results, advertisements, or chatbot responses; creating prompts for large language models; and reviewing cultural and linguistic accuracy. Project duration, scope, timelines, and compensation vary. This is a talent community opportunity rather than an active job opening.

Join Welo Data’s Russian-language AI contributor network for flexible, remote projects involving text, image, and audio annotation; search, ad, and chatbot evaluation; prompt creation; and cultural and linguistic quality review. This is not an active opening. Contributors are contacted when suitable projects become available and receive project-specific details about tasks, timelines, and compensation.

Join Welo Data’s Basque contributor network for potential remote AI projects involving data annotation, search and chatbot evaluation, prompt creation, and linguistic or cultural quality review. Projects vary from several days to weeks, with scope, timelines, and compensation provided before participation. This is a talent-network opportunity rather than an active job opening.

Lead research and production development of LLMs and transformer models for machine translation and language quality. Design evaluation frameworks, agentic NLP workflows, training pipelines, and model-provider strategies. Own flagship model programs from data curation through production integration, mentor researchers, review technical work, and collaborate with Product and Engineering to ship capabilities. The role requires deep NLP and LLM expertise, rigorous experimentation, strong Python and ML library skills, and technical leadership.

Lead the creative team to develop visually striking concepts across CGI and motion design, ensuring high-quality output and innovative storytelling while collaborating on business pitches and client briefs.

Lead 0-to-1 product development for Kimchi’s AI coding and infrastructure products. Responsibilities include identifying high-value customer problems, conducting discovery, validating hypotheses, prioritizing opportunities, partnering with engineering and design, defining success metrics, driving adoption, and communicating product direction. The role requires strong judgment in ambiguous, rapidly changing technical markets and hands-on use of modern AI tools.

Lead engineering execution and technical direction while remaining approximately 75% hands-on. Responsibilities include developing LLM- and AI-powered products, coding, code review, debugging, platform performance, sprint planning, cross-functional coordination, technical mentorship, recruiting, and supporting engineers’ growth. The role partners closely with founders and product teams and offers a path toward Engineering Manager responsibilities.

Own product areas for AI Stockbroking and other financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, compliance, operations, and business teams; simplify complex financial products; launch features; monitor performance; and continuously improve products using data, research, feedback, and production insights.

Leads global commercial customer data governance, Customer 360 strategy, segmentation, data quality, reporting, and insight initiatives. Owns customer definitions and hierarchies across SAP and Salesforce, establishes governance and KPI standards, and aligns reporting and analytics investments with business value. Partners cross-functionally to improve data quality, reporting adoption, forecast accuracy, and AI readiness while driving change management and value realization across the commercial organization.

Own AI Investing product areas across financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams. Simplify complex financial workflows, launch and monitor features, analyze feedback and performance, and drive iterative improvements while balancing speed, user experience, business impact, compliance, and operational complexity.

Designs and leads AI infrastructure solutions for enterprise customers, from use-case ideation through implementation and Proof of Value projects. Architects scalable, secure environments using AI-optimized networking, compute, and observability technologies. Aligns Cisco’s AI stack with ecosystem partners, advises technical and executive stakeholders, supports technical sales engagements, and provides product roadmap feedback. Requires systems engineering or solution architecture experience, Kubernetes and microservices expertise, networking and security knowledge, and strong technical communication skills.

Lead AI transformation across Sales, Marketing, Customer Success, Partnerships, and Revenue Operations. Identify high-value opportunities, design and deploy production AI agents, agentic workflows, automations, integrations, and enterprise solutions, then drive adoption and measure business impact. Partner with functional leaders, make sound decisions about AI suitability, redesign operating models, improve reliability and governance, and mentor colleagues while establishing reusable standards across the organization.

Own product marketing for Cyara’s Agentic AI assurance products, including positioning, messaging, go-to-market launches, competitive intelligence, sales enablement, technical content, and cross-functional collaboration. The role targets enterprise buyers through sales-led motions and requires measurable pipeline impact, strong writing and presentation skills, and comfort working with technical teams. Experience in AI, contact centers, QA, testing, observability, or monitoring is advantageous.

Own end-to-end infrastructure delivery for strategic physical AI customers, from discovery and architecture through production rollout. Build cloud compute orchestration, platform services, onboarding environments, observability, security, and cost controls for simulation, training, inference, and batch workloads. Debug across infrastructure layers, productize recurring customer needs, and shape the physical AI platform roadmap. Partner with customers, Field CTO, Product, and Engineering while using AI coding tools to accelerate production engineering.

Own vendor and outsourcing-partner relationships and customer-service operations across support channels. Lead governance, business reviews, escalations, service delivery, SLA and quality performance, campaigns, incident and compliance management, and continuous improvement. Drive AI and automation initiatives that improve efficiency and customer experience while supporting training, knowledge sharing, and best-practice adoption. The role requires regular visits to partner contact centers and fluent Dutch.

Lead field-facing AI security strategy for enterprise customers: design secure LLM/RAG architectures, deliver demos/POVs, advise on data protection and governance, and scale enablement across sales and product teams.

Architect and build the AI layer for Neo4j’s Hume Maestro platform. Responsibilities include setting the AI technical roadmap, contributing hands-on to production code, designing scalable AI architectures, establishing model evaluation and deployment practices, integrating AI with front-end and platform systems, and collaborating with Product and Science stakeholders. The role may eventually evolve into leading and mentoring a dedicated AI engineering team.

Build Python-based backend services, APIs, and integrations that embed AI capabilities into a SaaS platform. Develop scalable customer-facing features, connect AI outputs to workflows and dashboards, collaborate with product, design, and platform teams, and implement observability, monitoring, and error handling. Contribute to the AI integration stack, including SDKs, MCP servers, and LLM orchestration.

Join Welo Data’s global contributor network for flexible, remote AI projects. Depending on skills, contributors may annotate text, images, or audio; evaluate search results, advertisements, and chatbot responses; create prompts; and assess cultural and linguistic accuracy. Projects vary from several days to weeks, with compensation and requirements provided before each assignment.

Own Soda’s technical content function across its website, blogs, webinars, videos, and audience growth. Build automated, agentic LLM content pipelines with structured outputs and evaluations while maintaining strong editorial judgment, distinct voices, and high-quality technical writing. Develop independently using Python or TypeScript, APIs, webhooks, and databases. Translate data quality and infrastructure concepts for technical audiences, collaborate with founders and customer engineers, and continuously improve workflows based on content performance.

Lead the design, build, and deployment of AI-powered agents, workflows, and integrations for global marketing. Evaluate buy-vs-build, integrate platforms (HubSpot, Salesforce, Meta, Google, LinkedIn), optimize AI economics, and measure ROI while collaborating with marketing teams to automate and improve campaign execution and content localization.

Lead the company’s Physical AI research and engineering function as a hands-on technical leader. Define research priorities, design and train Transformer-based models, establish rigorous offline and real-world evaluations, integrate systems with physical robots, and analyze failures across data, models, hardware, and environments. Build a focused team, guide technical architecture and experiments, translate customer needs into requirements, and deliver measurable improvements through deployed models, benchmarks, evaluation systems, or data products.