Top Artificial Intelligence Jobs in Amsterdam

Develop intelligent agents for a materials discovery engine, orchestrating scientific workflows and integrating experimental design for sustainability solutions.

As an AI Research Intern, you will tackle AI research questions, build prototypes using AI tools, and design evaluations for AI systems while collaborating with fellow engineers and product managers.

Lead product direction and execution for major AI Neobank app areas. Define roadmap, priorities, metrics, and standards across squads. Mentor PMs, align cross-functional teams, translate regulatory/operational constraints into product decisions, drive launches, post-launch learning, and continuous improvement in fintech products.

Own and deliver product areas within an AI neobank app: define problems, scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance and business teams to simplify complex financial products, run experiments, monitor performance, and iterate post-launch to improve user experience and business outcomes.

Build and scale AI-driven automation solutions using LLMs and agent frameworks. Design multi-step workflows, integrate AI with internal systems (HR, finance, legal, ticketing), automate document processing and data extraction, and train internal teams. Collaborate with technical leads, product, and IT to deliver practical, production-ready automation and iterate quickly.

Work directly with agentic AI infrastructure to improve resolution quality while independently resolving escalated technical support tickets via log analysis, API debugging, and coordination with Engineering. Maintain and enhance the technical knowledge base, track recurring issues for Product/Engineering, and contribute to onboarding and training of new support team members.

Lead the company’s ML/AI platform from experimentation through production, including SageMaker training infrastructure, model serving, inference pipelines, MLOps, and Java microservice integrations. Set AI/ML technical direction, develop GenAI and LLM retrieval and agent architectures, establish evaluation and safety guardrails, and partner with data science, DevOps, product, and engineering leadership on scalable ML roadmaps.

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.

Develop and optimize AI pipelines for workflow intelligence, experiment with models, and collaborate to integrate AI systems into workflows.

Build and ship native Android features for an AI-enabled neobank using Kotlin. Design clean user flows for payments, insurance, claims and financial services, integrate backend APIs, improve performance and reliability, use analytics and production feedback, and implement AI-assisted mobile experiences where they add real value.

Design, build and ship Kotlin-based Android features using Jetpack Compose and Android SDK. Integrate REST APIs, improve performance, crash rates, memory usage and responsiveness. Collaborate with product and design to simplify complex financial user journeys, use analytics and production issues to iterate, and implement AI-assisted on-device experiences where beneficial.

The AI Engineering Intern will design, test, and deploy scalable AI systems, integrate models, and work on inference optimization, collaborating with data scientists on complex problems.

The Applied Scientist will solve impactful problems using deep learning models and statistical analysis, translating commercial goals into technical solutions.

AI Engineers at QuantCo design, build, and implement applied AI systems, working with data scientists to optimize inference, develop scalable solutions, and integrate AI into enterprise operations.

As a Senior AI Engineer, you will develop AI-powered features, integrating LLM APIs to enhance user workflows while collaborating with teams to ensure reliability and scalability.

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 Senior AI Product Manager will lead cross-functional teams to define, develop, and manage B2B SaaS products, focusing on customer value and market needs, while utilizing Agile methodologies and Generative AI technologies.

Perform remote, part-time data tasks to improve Dutch AI outputs: collect, evaluate, and annotate data; perform pairwise comparisons, counting, object tagging across audio, video, images, and other content.

Develop AI agents, enhance workflows, and evaluate generative AI models. Build APIs and optimize knowledge systems in a fast-paced environment.

Design, build, and deploy production AI agents in Python, integrate with enterprise systems, evaluate and maintain agent performance, and collaborate cross-functionally while producing well-tested, documented code and CI/CD pipelines.

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 global channel strategy for AI-native networking, enabling partners to deliver AI-optimized infrastructure, automation, and security. Define standards for partner specialization, drive partner readiness and investments, represent HPE at partner and industry events, and align cross-functional teams to scale repeatable AI networking deployments and self-driving network models.

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.