Top Artificial Intelligence Jobs in the Netherlands

Own Qogita’s supplier acquisition function, including strategy, pipeline, forecasting, quotas, systems, compensation, and team performance. Lead and coach SDRs and Account Executives acquiring wholesalers and distributors across Europe. Improve supply growth through AI agents, automation, lead scoring, and data-driven processes. Manage initiatives against GMV and supply-quality goals while building a scalable B2B marketplace sales organization.

Own the Vault product roadmap and lifecycle for a sports media asset platform. Lead discovery with customers, define solutions for content ingest, storage, integrations, AI enrichment, metadata, search, rights, and asset monetization. Partner closely with engineering, sales, and customer success, attend customer events, and prioritize product bets that help sports organizations maximize the value of extensive media archives.

Drive pipeline growth through outbound prospecting, inbound lead follow-up, qualification meetings, account research, and personalized outreach. Use sales tools to identify decision-makers, engage manufacturing prospects, and transfer qualified opportunities to account executives. Collaborate with sales and marketing, manage event leads, maintain CRM records, gather market insights, and continuously optimize outreach strategies.

Drives new-logo revenue across the Benelux mid-market by prospecting, managing complex 6–9 month sales cycles, engaging senior finance stakeholders, presenting ROI-driven solutions, negotiating contracts, forecasting pipeline, and exceeding quota. The role requires consultative SaaS selling, strategic account planning, executive communication, and collaboration with Sales Engineering, Marketing, Customer Success, and Product teams.

Lead the architecture and development of production LLM agents for a legal AI platform. Design agent workflows, scalable knowledge pipelines, evaluation and observability systems, backend integrations, and quality metrics. Explore emerging AI techniques, identify technical risks, prioritize work, and coach engineers while collaborating with legal editors and subject-matter experts.

Build and improve production LLM agents for a legal AI platform. Develop knowledge packages and update pipelines, create evaluation and observability systems, build REST APIs and customer-facing AI features, and collaborate with lawyers and editors to improve answer quality, source attribution, and reliability.

Architect and build Together AI’s globally distributed GPU cloud platform, including virtualization, Kubernetes-based IaaS, GPU scheduling, networking, storage, fault-tolerant control planes, monitoring, and automated remediation. Set technical direction, lead architecture and design reviews, drive cross-team alignment, mentor engineers, and establish engineering standards for reliable, high-performance AI infrastructure at massive scale.

Senior Solution Engineer supporting the Netherlands market by partnering with account sales teams, channel partners, and customers throughout the sales cycle. Responsibilities include presenting Snowflake to technical and executive audiences, delivering demonstrations and proofs of concept, designing architectures, developing technical champions, supporting account strategies, and positioning Snowflake against competing technologies. The role also involves collaborating with Product, Engineering, Marketing, and implementation partners while maintaining expertise in data, cloud, AI, and analytics technologies.

Leads social media and content strategy across markets, owning editorial planning, content distribution, creator programs, community management, and performance analytics. Builds and operates AI-enabled content workflows, coordinates agencies and creators, and turns audience and channel data into measurable demand-generation decisions. Partners with brand, product marketing, performance, and country teams to scale platform-native content across TikTok, YouTube, Meta, and LinkedIn.

Own the customer journey from onboarding through retention and expansion for B2B SaaS customers in audit and finance. Act as a strategic advisor, drive product adoption and value realization, lead training and business reviews, develop success plans, monitor customer health, support technical implementation, and identify growth opportunities. Collaborate cross-functionally with Product, Engineering, Sales, and Solutions Engineering while advocating for customer needs.

Lead technical authority for generative AI, designing production-grade LLM solutions for digital-native customers. Responsibilities include RAG and agentic architectures, fine-tuning, evaluation, proofs of concept, MLOps implementations, customer consulting, product feedback, technical enablement, mentorship, and external thought leadership across EMEA.

Leads clinical AI strategy, validation, safety evaluation, and deployment of clinical decision-support solutions. Partners with product, engineering, editorial, business development, customers, and strategic partners to ensure clinically accurate and trustworthy implementations. Designs clinical outcomes studies, translates clinical feedback into product improvements, monitors evidence and regulatory developments, and represents the company through thought leadership. Optional clinical practice may comprise up to 20% of the role.

Designs enterprise SIEM and security solutions using Elastic Security and AI, delivers proof-of-value projects, supports incident response, and presents to technical and executive audiences. The role requires deep SOC workflow expertise, security architecture knowledge, forensic analysis, threat mitigation, behavioral analytics, consultative selling, and customer-facing presentations. Candidates must be fluent in Dutch and willing to travel 30–50% of the time.

Own production Python data pipelines, ETL/ELT workflows, and the ontology powering an AI platform. Integrate warehouses and business applications with graph databases and vector stores, while managing deployment tooling, cloud infrastructure, monitoring, and security. The role begins as hands-on individual contribution and develops toward technical leadership through mentoring and architecture ownership.

Build and scale the infrastructure that moves AI systems from experimentation to reliable production. Responsibilities include developing an AI gateway with routing, fallbacks, privacy controls, and cost attribution; standardizing tracing, evaluation, benchmarking, and monitoring; productionizing open-weight models for fine-tuning and serving; and providing APIs, SDKs, templates, and tooling for agent development. The role requires strong Python backend engineering, cloud infrastructure, Kubernetes, observability, and cross-functional ownership.

Develop and deploy spatial perception models for ADAS/AD, including BEV and occupancy-based architectures. Lead large-scale distributed training, synthetic data validation, model quantization, compression, and edge optimization for automotive SoCs. Translate research into production pipelines, benchmark accuracy and performance, conduct experiments, and build regression testing. Collaborate with research and engineering teams while mentoring junior engineers and maintaining high standards for code quality and documentation.

Build and lead n8n’s internal AI and automation enablement function. Run recurring workshops, office hours, build-alongs, bounty hunts, hackathons, and dogfooding initiatives for technical and non-technical teams. Develop reusable templates, measure AI fluency and adoption, support cross-functional champions, and act as product owner for a safe internal automation playground. Partner with IT, Security, Data, and Solutions Engineering to define access, credential, and environment requirements.

Create short films and videos using AI photo and video generation tools. Edit AI-generated content, develop concepts with marketing teams, maintain brand alignment, experiment with creative formats, and deliver engaging content for Tether and affiliated brands. The role requires video production and editing expertise, strong storytelling and visual composition skills, familiarity with digital marketing and social media, and the ability to manage multiple projects independently under tight deadlines.

Design and implement cloud-based data solutions and scalable data pipelines for financial services clients. Migrate legacy Excel models to Azure, support AI/ML and LLM integrations, develop data architectures, and collaborate with consultants and actuaries to productionize analytical applications while applying software engineering best practices.

Designs and publishes networking architectures for large-scale GPU clouds and AI infrastructure. Defines InfiniBand and RoCEv2 fabrics, multi-tenant isolation, Kubernetes and KubeVirt networking, hybrid connectivity, and host networking. Builds automation, prototypes, proofs of concept, and benchmarks on real hardware. Acts as a customer-facing networking subject matter expert, collaborates with partners, conducts research, publishes technical content, and influences product strategy.

Build examples, integrations, tooling, and documentation for Toqan, Prosus’s agentic AI platform. Reproduce bugs, contribute fixes, support developers, review pull requests, and convert community feedback into engineering improvements. Create technical content, demos, talks, workshops, and events to grow adoption. The role requires production software engineering experience, hands-on agent and LLM expertise, MCP familiarity, cloud experience, and strong public technical communication skills.

Supports Account Executives throughout the sales cycle by leading technical discovery, solution design, demonstrations, workshops, proofs of concept, evaluations, and technical validation. Translates engineering, simulation, HPC, AI, and infrastructure requirements into Rescale recommendations, documents opportunities in Salesforce, resolves technical risks, supports negotiations, and ensures effective post-sale handoffs across Northern Europe.

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.

Operate and scale multi-petabyte distributed storage for AI and HPC workloads. Design high-performance parallel filesystems, object stores, caching architectures, and Kubernetes-native storage operators. Optimize data paths, throughput, multi-tenancy, cost, and reliability across thousands of GPU nodes. Integrate technologies such as Vast, Weka, Ceph, and Lustre; develop automation and tooling in Go and Python; and contribute to storage infrastructure, observability, benchmarking, and open-source projects.

Design, implement, and optimize high-performance attention and foundational AI kernels for GPUs, NPUs, ASICs, and other accelerators. Build reusable attention-framework abstractions, profile workloads, develop benchmarks and correctness tests, analyze hardware and compiler behavior, and improve production inference performance. Collaborate with hardware and software teams, document designs, resolve ambiguous performance issues, and mentor engineers while supporting new accelerator architectures and AI workloads.