Top Artificial Intelligence Jobs in Amsterdam

As an AI Product Manager, you will define the product roadmap, collaborate with teams to develop AI features, conduct market research, and ensure ethical AI use.

Seeking an AI/ML Engineer to develop and optimize machine learning models for mobile apps, collaborating with teams to enhance user experiences.

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.

Build and operate shared AI platform infrastructure for LLM applications, agents, RAG, tool calling, and AI workflows. Develop data and knowledge pipelines, secure enterprise integrations, reusable frameworks, deployment and observability standards, and developer tooling. Take AI systems from experimentation to reliable production while ensuring security, privacy, governance, scalability, quality, and cost efficiency. Collaborate across Engineering, Product, and IT to establish practical AI platform patterns and guardrails.

Own the learner journey across discovery, enrollment, and learning for an AI-native university. Build and iterate consumer products, use AI tools to ship quickly, and improve retention, engagement, and conversion. The role requires technical fluency, comfort with APIs and model trade-offs, strong execution in ambiguity, and experience managing a team. Success is measured by learner return and engagement rather than feature volume.

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.

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.

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.

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.

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.

As a Staff/Senior AI Product Engineer, you will build AI-powered product features, enhance the tech stack, and design AI workflows while collaborating with product teams. Your focus will be on agent-native architecture and improving the codebase for AI agents.

Design, develop, and deploy AI-powered enterprise applications using Python, LLMs, RAG, and vector/semantic search. Build scalable backend services and RESTful APIs, handle structured and semi-structured data, perform data analysis and validation, collaborate with stakeholders, ensure governance/security, and participate in Agile delivery and continuous improvement.

Design, build, and deploy scalable AI/ML and Generative AI solutions for enterprise systems. Develop Python-based production applications, APIs, microservices, and MLOps/CI-CD pipelines. Implement data ingestion, preprocessing, feature engineering, model training/validation, deployment, monitoring, and lifecycle management. Collaborate with DevOps, data engineering, and product teams to ensure secure, compliant, and high-performance AI solutions.

Technical Business Analyst responsible for gathering, documenting, and translating business and technical requirements for Azure DevOps, CI/CD, AI, and platform engineering initiatives. Manage Azure DevOps Boards, define user stories and acceptance criteria, support Agile delivery, collaborate with DevOps, AI, and platform teams, and drive automation, release readiness, and end-to-end requirement traceability.

Lead enterprise adoption of GitHub Copilot and AI-assisted developer tools, providing hands-on guidance, troubleshooting integrations, defining best practices, running enablement sessions, measuring adoption and productivity, and aligning implementations with security, governance, and DevOps practices.

Lead technical delivery and architecture of enterprise ServiceNow solutions across ITSM, CSM, HRSD, and CMDB. Design Agentic AI (MCP) solutions, integrations (REST, MID Server, IntegrationHub), server-side scripting (Glide Script), workflows (Flow Designer), and automated tests (ATF). Provide technical leadership, run discovery workshops, perform architecture/code reviews, mentor consultants, and resolve complex delivery challenges.

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.

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.

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.

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.

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.

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.