Top Artificial Intelligence Jobs in Amsterdam

Design and implement agentic tools, translating product needs to production, scale prototypes, improve semantic search, build evaluation pipelines.

Lead design and delivery of AI-powered features for CLion and C++ workflows. Architect AI integrations and agent tools, prototype and validate debugging, code-understanding, refactoring, and navigation workflows, build benchmarks and evaluation frameworks, and collaborate with product, ML, QA, and engineering teams to set technical direction and roadmap for AI-assisted C++ development.

Coordinate and track clinical AI projects across Product, Engineering, Clinical, and Operations. Maintain project plans, trackers, risk logs, and regulatory/compliance documentation (MDR, GDPR). Support planning, reporting, audit readiness, and cross-functional communication to ensure timely, on-scope delivery.

Own end-to-end product for a slice of Nebius AI compute platform: define strategy, APIs, and roadmaps; drive cross-team delivery; conduct structured discovery; measure adoption and platform outcomes; engage engineering as a technical peer; and close operational feedback loops to improve reliability and customer experience.

The Site Reliability Engineer ensures user-facing services run smoothly, focuses on systems reliability and scalability, and enhances operational practices through automation and engineering principles.

Define and execute the product roadmap for AI-driven blockchain security monitoring tools. Collaborate with cross-functional teams, analyze market and customer feedback, deliver features on time, and communicate with stakeholders to align expectations and improve product offerings.

Lead applied research and system design for agent-native search: build multi-stage retrieval, ranking, and grounding methods for LLMs over real-time web data, design evaluation metrics, run experiments, deploy high-throughput low-latency systems, and mentor engineers.

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.

Lead a 4-person Data & AI team to define strategy, prioritize projects, set tech and governance guardrails, and deliver high-impact analytics and AI solutions. Split time between coaching the team and hands-on work (data modelling, capacity forecasting, pricing/AI prototypes), and enable the organisation to adopt AI responsibly and practically.

Design and implement execution primitives for AI/agent workflows in Kestra's Java core, build and maintain plugins to connect LLM providers and agent frameworks, convert agent use cases into reusable blueprints with product, and ensure AI executions are observable, debuggable, correct, and reliable.

Own AI workflows product: discover and validate AI use cases with customers, define roadmap and specs, create reusable blueprints with engineering, and prioritize what not to build.

As an AI-native growth hacker, you will implement a growth strategy, focusing on a specific growth wedge, leveraging AI tools, and measuring performance to scale successfully.

Lead strategic AI adoption for enterprise customers across EMEA by designing, prototyping, and implementing agentic and conversational AI solutions. Drive discovery, architecture, POC/MVP delivery, evaluation frameworks, governance, and handover while mentoring teams and shaping product and roadmap decisions to achieve measurable business outcomes.

Design polished, mobile-first interfaces and prototypes for BJAKs AI and financial products. Translate requirements into wireframes, flows, and high-fidelity UI, maintain the design system, collaborate with PMs and engineers, iterate from user feedback, and ensure accessibility and responsiveness across devices.

As a Staff/Senior AI Engineer, you will develop production-ready coding agents and improve AI model capabilities for JetBrains' software development tools. Collaborating with teams, you'll focus on model training, evaluation, and product integration to enhance user experience.

As a Senior Software Engineer, you will design and implement AI-powered agents to automate assurance workflows and build production-ready solutions. You'll collaborate with product teams to enhance the development process and maintain high standards in code quality and architecture.

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Hands-on lead full-stack engineer who designs scalable architecture, ships production SaaS features, integrates AI tools, mentors senior engineers, improves deployment pipelines, and drives engineering quality.

Create high-converting image and video content for e-commerce ads and product campaigns, optimize creatives for CTR and conversions, run end-to-end campaign design, and scale production using AI tools while maintaining brand consistency.

Lead development and scaling of AI-powered clinical applications using LLMs. Gather user and industry requirements, write product specifications, prioritize roadmaps, coordinate sprints and releases, validate quality with engineering and QA, and design generative AI capabilities to streamline pharmaceutical workflows and regulatory documentation.

Build and own the AI platform that enables fast, safe shipping: prototyping sandbox, CI/CD pipelines, automated tests and evals, agent runtime and orchestration, AI tooling, observability, and reliability. Drive platform standards, quality gates, and production-safe agent workflows so builders can ship rapidly and confidently.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

Partner with Account Executives to present Arize's GenAI observability platform, lead technical demos and discovery, design and run PoCs, advise on GenAI/LLM best practices, handle technical objections, and build relationships with technical and business stakeholders across prospective customers.

As an AI Research Engineer, you will focus on model compression techniques to enhance performance of AI systems, ensuring efficient deployment on edge devices while maintaining accuracy.

Drive innovation in post-training methodologies for AI models, focusing on agentic behaviors, tool use, and enhancing model capabilities for real-world applications.