Top Artificial Intelligence Jobs in Amsterdam

As an AI Automations Engineer, you will design and build tooling for GTM, Operations, and Finance teams, automating processes and enhancing systems with a focus on AI.

The Senior AI Engineer will design and develop advanced ML and NLP solutions for healthcare, collaborating across teams and mentoring juniors.

Own global TA operations, tech stack, data and workflows; build dashboards and automations; run interviewer enablement; partner on AI pilots and governance; ship low-code tools and integrate AI into recruiting processes to improve time-to-fill and recruiter productivity.

Lead EMEA go-to-market for Physical AI by sourcing executive-level pipeline, accelerating top accounts, building EMEA-specific playbooks, enabling regional sales, and converting lighthouse wins into sustained cloud consumption across robotics, autonomy, simulation, and related AI-native industries.

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 acquisition, onboarding, and activation for JetBrains AI. Improve product entry points, trials, demos, and onboarding flows. Lead experiments, analyze funnels and cohorts, remove friction, and partner with design, engineering, analytics, marketing, and monetization to drive activation and conversion.

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

Design, build, and maintain production-grade AI services and APIs using LLMs and custom models. Develop agentic orchestration, semantic retrieval, and vector-search systems. Implement scalable Python microservices, shared libraries, observability, and CI/CD. Collaborate across product and platform teams, conduct performance tuning, and mentor engineers throughout the full software lifecycle.

Own the AI platform roadmap and build reusable capabilities (prompting, RAG, tool calling, agents, evaluation, observability). Run discovery, prioritize AI investments, partner with Product, Engineering, Design and Data, guide other PMs, define success metrics, and ensure scalable, reliable AI-powered features that deliver customer and business value.

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.

Own the end-to-end process converting product, marketing, and account signals into qualified sales opportunities. Build qualification criteria, routing rules, data enrichment and automation, partner across product/marketing/sales/analytics, create feedback loops, and measure and optimize funnel conversion and data quality.

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.

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.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Work within the Creative Studio/Technology team to design and build AI agents and image-processing pipelines. Prototype and integrate generative AI and computer-vision models into production workflows, develop tooling, and deliver tasks from brief to deployment while collaborating with designers and creatives.

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.

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.

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.

Own AI search and reputation for Jabra: audit AI answer engines and search, prioritize external citation sources, brief teams, optimize jabra.com for citation (structure, schema, entities), and track answer visibility and citation quality.

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.

Provide cloud and AI technical consulting, design solutions and migrations on Tencent Cloud, support pre-sales and cross-functional project coordination, enable partners via training, and document industry-specific use cases.

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

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.

As an AI Research Engineer, you'll optimize model deployment and inference architectures for AI systems, enhancing performance across various applications, especially on resource-constrained devices. Responsibilities include designing efficient serving architectures, conducting inference tests, and collaborating with teams to integrate solutions.

As an AI Research Engineer, you will develop multi-modal reinforcement learning systems, focusing on optimization across data modalities, conducting research on algorithms, and building infrastructure for scalable training and evaluation.