Top Artificial Intelligence Jobs in the Netherlands

The Senior Consultant will manage digital transformation projects, focusing on strategy, marketing excellence, and customer experience. They will collaborate globally while ensuring project quality and governance.

Lead research and deliver executive-level insights on enterprise AI strategy, producing thought leadership, advising clients and vendors, supporting sales and conferences, mentoring analysts, and driving research agenda and process improvements to accelerate clients' AI value realization.

Lead government affairs strategy and engage with public sector leaders in the UK and EU, educating on cloud and cybersecurity policies.

Own partnership sourcing, negotiation, and deal execution to drive adoption of Walrus across AI and Web3 ecosystems. Build relationships with AI builders, data vendors, compute networks, and web3 partners; lead contract negotiations; and manage cross-functional integration from signing through execution.

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.

Design, build, monitor and optimize responsible Generative AI solutions for financial clients. Focus areas include performance monitoring, red‑teaming, fairness and bias evaluation, reusable GenAI building blocks, APIs, and collaboration with stakeholders to deliver cost‑effective, scalable 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.

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.

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.

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.

Design, build, and maintain automated test suites, evaluation scenarios, metrics, and datasets for AI-powered features. Automate QA workflows with Python and CI/CD, test APIs and ML model outputs, define quality strategy and acceptance criteria, create CI/CD quality gates, mentor teams, participate in code reviews, and document findings.

Design, build, and operationalize AI/ML solutions from assessment through production. Develop scalable data, DevOps/MLOps pipelines, customize deep learning and generative models (including LLMs), work with large datasets and HPC/distributed systems, collaborate with cross-functional teams, and justify business value of model approaches.

Evaluate and label AI-generated images, videos and designs in Dutch for linguistic quality, accuracy and cultural appropriateness. Build Dutch datasets, meet output targets, refine labels from feedback, and collaborate with global data labelling teams.

The Major Account Manager drives sales in a targeted list of Fortune 500 accounts, developing and executing account plans while maintaining relationships with stakeholders. Responsibilities include consultative selling of networking solutions and business planning to meet customer needs.

Hands-on platform engineering role building and operating an internal Agentic AI platform: implement infrastructure-as-code, security and secrets management, GitOps delivery, observability, autoscaling, API/AI gateway routing, and run day-to-day operations including incident response, backups, and runbooks.

Design, build, and operate the AI storage layer for GPU-heavy edge and core deployments. Architect and optimize storage for distributed training and inference, integrate storage with Kubernetes (CSI), tune performance (RDMA, NVMe-oF, GPU Direct Storage), lead reliability and operational practices, and provide staff-level architectural ownership and cross-team influence while executing hands-on storage engineering.

Own design, deployment, and operation of high-performance AI GPU fabrics and datacenter networking (RoCE, RDMA, BGP/ECMP, EVPN/VXLAN). Provide staff-level architecture, cross-team technical leadership, incident escalation, automation (Python/Bash), and operational standards for global datacenter and edge deployments, including inter-datacenter transport and security.

Provide research and advisory to global CFOs and Controllers on transforming controllership processes (AP, AR, financial close) using AI, automation and finance technologies; produce published research, vendor evaluations, and client-facing presentations; collaborate with analysts and deliver strategic, actionable recommendations to improve financial reporting and automation outcomes.

The Business Process Expert focuses on applying AI to enhance service delivery, processes, and outcomes while ensuring quality and compliance in operations.

Lead design quality engineering for AI-enabled medical software across the product lifecycle. Drive compliance with ISO/IEC and AI frameworks, oversee AI model validation, risk analyses, design reviews, testing automation, and mentor teams to ensure traceability, reliability, and regulatory readiness.

Lead product development in the industrial sector focusing on IoT, edge computing, and AI applications. Oversee product lifecycle, conduct market research, and collaborate with cross-functional teams.

Drive end-to-end GPU + networking reference architectures and pre-sales integration for NVIDIA AI Cloud Partners. Lead technical account engagements, POCs, performance troubleshooting, roadmap presentations, and project management for complex datacenter networking deployments.

Own and grow the Data Layer: build and operate ingestion, transformation, reconciliation, and serving pipelines (raw→refined→curated). Use agentic AI tools to accelerate delivery, ensure data correctness, and partner with backend, AI, and product teams to define reliable data contracts.

Design, build, and maintain a central GenAI (LLM) Gateway and production-grade GenAI applications on Azure. Implement CI/CD with Azure DevOps, manage LLM model lifecycles, use IaC, containers and vector DBs, and integrate AI capabilities into business systems while collaborating with stakeholders and domain experts.

Join as an early-career full stack engineer to build frontend and backend product features, integrate AI coding tools into development workflows, translate product requirements into implementations, and grow toward autonomous full stack delivery while improving cross-team processes.