Top Artificial Intelligence Jobs in the Netherlands

Conduct applied AI/ML research to solve home design challenges, work with raw data, test hypotheses, and build prototypes/MVP solutions.

The role involves delivering features across the CRM platform for distributors, using AI tools, handling fullstack development tasks, and collaborating closely with teams and customers.

The AI Go-to-Market Engineer will deploy and optimize AI agents across Flosum's revenue operations, enhance productivity and sales processes, and create AI-driven systems for customer engagement and competitive analysis.

The role involves leading design for AI-native products at Synthesia, focusing on improving interaction patterns and enhancing user experience in AI-driven workflows.

Lead Data, Analytics, AI, and GenAI presales activities for strategic enterprise opportunities. Facilitate discovery workshops, translate business needs into scalable architectures, lead RFP and RFI responses, and present solutions to executives. Design end-to-end AI and cloud architectures across Azure, GCP, Databricks, and open-source ecosystems. Advise on AI transformation use cases, roadmaps, governance, and implementation, while mentoring delivery teams and developing reusable frameworks, offerings, thought leadership, and customer success materials.

Develop and deploy production-ready generative AI applications using Python, LLMs, RAG, AWS Bedrock, and OpenAI APIs. Responsibilities include model customization, API integration, data preparation, performance tuning, production deployment, documentation, and cross-functional collaboration. The role focuses on applied engineering rather than research and requires experience integrating AI solutions into business applications.

Lead end-to-end client discovery engagements focused on AI, automation, and digital transformation. Facilitate stakeholder workshops, map processes and data landscapes, identify high-value opportunities, develop ROI-based business cases and phased roadmaps, and present recommendations to senior decision-makers. Bridge clients with product, engineering, and design teams while helping standardize and scale the discovery practice. Use AI tools for transcript analysis, rapid prototyping, and documentation.

Design and lead enterprise-scale data and AI architectures for global clients. Develop prototypes and proof-of-value demonstrations, govern AI agents, integrate cloud platforms and external systems, support pre-sales, establish technical standards, and mentor teams. The role requires translating business needs into secure, scalable technical solutions while driving cloud data platform adoption, data governance, modeling, and AI-driven transformation.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Lead design and early implementation of secure, scalable AI, analytics, and automation environments. Evaluate technologies, define architecture and governance, coordinate cross-team initiatives, enable early adoption, and transition solutions to operational teams. Ensure operational readiness, compliance, and long-term maintainability while remaining hands-on for prototypes and early integrations.

Own the full B2B sales cycle for Creative Fabrica’s API and AI platform, from prospecting and qualification through technical evaluation, negotiation, and closing. Build pipeline, convert inbound and founder-sourced opportunities, coordinate proof-of-concepts, support procurement and security reviews, and establish the company’s initial sales processes, CRM structure, forecasting routines, pricing, positioning, and playbook.

Own and build Polaroid’s People Operations function, including HRIS architecture, people data, employee lifecycle processes, compliance, payroll inputs, benefits, and mobility support. Lead cross-functional projects and modernize employee services through AI automation, workflows, chatbots, and policy knowledge bases. Manage HR technology integrations, data quality, dashboards, compensation cycles, and employment-law processes across jurisdictions while partnering with Finance, IT, Legal, Payroll, and Talent Acquisition.

Build and improve Restream’s web interfaces and user-facing features for the AI Clips team. Design UI and business logic, collaborate with product designers, participate in code reviews, improve system reliability, and evaluate emerging technologies. The role requires strong JavaScript and TypeScript expertise, advanced React knowledge, CSS preprocessor experience, and familiarity with backend development, cloud infrastructure, containers, and continuous deployment.

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.

As a Chatdesk Expert, you will provide customer support via social media and email, representing brands and resolving customer inquiries professionally.

Embed on-site with mid-market CEOs to lead Valis AI deployments: own executive relationships, run transformation cadences, drive fast fixed-scope wins, translate problems into build-ready specs, ensure finance-verified P&L outcomes, manage end-to-end rollout and adoption, and codify repeatable deployment methods.

Create high-volume, high-quality marketing content using generative AI and AI agents. Produce video, image, and social content, develop attention-driving campaigns, track AI and culture trends, and iterate quickly with the marketing and founding team.

Lead design and ownership of shared libraries, Spring Boot starters, and agentic frameworks. Set standards for agent orchestration, evaluations, and guardrails. Mentor teams on Python-based agents (LangChain/LangGraph), drive adoption, prototype research directions, and improve developer experience across Kotlin backend and client libraries.

Lead AI-focused consulting engagements, build C-suite relationships, drive profitable growth and business development, oversee multi-disciplinary delivery, ensure operational excellence and utilization, shape strategic initiatives and thought leadership, and mentor talent to deliver transformational Data & AI and cloud solutions.

Provide EU-focused counsel on AI and privacy regulation (EU AI Act, GDPR, DSA); draft policies, DPA and contractual terms; translate legal requirements into technical and operational controls; advise product, engineering, and go-to-market teams; liaise with regulators and manage compliance programs and risk assessments.

Develop and maintain front-end and back-end AI-enabled web and desktop applications. Collaborate with cross-functional teams to design features, optimize scalability and security, troubleshoot defects, participate in code reviews, and implement AI assistant technology integrated with enterprise systems.

Own the AI product vision, roadmap, prioritization, and delivery from ideation through launch. Translate business needs into technical requirements while collaborating with engineers, data scientists, marketers, and commercial teams. Drive AI adoption, monitor trends, define success KPIs, and ensure responsible, ethical, and privacy-compliant product usage.

Design and scale Go-based microservices that orchestrate high-concurrency, multimodal AI generation workflows. Optimize ConnectRPC services and Kafka/SQS asynchronous pipelines for long-running inference tasks, manage AWS infrastructure and high-throughput storage and compute, and collaborate with AI researchers to deliver reliable creative tools. The role emphasizes distributed systems, performance, observability, testing, and professional-grade media or creative applications.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Consults with banks, insurers, and asset managers to build and validate statistical, predictive, and generative AI models for financial risk, AML, fraud, sanctions, and regulatory compliance. Analyzes complex financial datasets, supports AI model governance, applies machine learning to transaction monitoring, and communicates findings directly to clients. The role also involves project ownership, regulatory research, internal knowledge sharing, and identifying improvements to clients’ financial technology practices.