Artificial Intelligence

• Lead ScreenPoint Medical’s AI enablement effort
• Identify internal workflows worth automating and prioritize what gets built
• Build AI-powered tools to accelerate internal workflows in collaboration with workflow-owning teams
• Apply security as a guiding principle throughout design and development
• Drive adoption by evangelizing AI tooling internally and helping colleagues and teams gain value from the tools
• Build internal production-grade tools, shipping quickly and iterating from proof of concept to daily-use solutions
• Integrate LLM/AI capabilities, including APIs, agents, RAG, and automation frameworks, into internal tools and pipelines
• Design, build, and maintain GitOps-based CI/CD pipelines
• Own and evolve Kubernetes-based infrastructure, including deployments, scaling, observability, and cost
• Take full ownership of solutions from idea through production support

AI Enablement Engineer

• Resolve technical hurdles for non-technical teams and enable colleagues to complete GenAI experiments
• Build practical GenAI prototypes and workflow automations
• Set up custom Gemini or Claude tools for daily operational challenges
• Develop and present tangible AI demos
• Inspire teams across Operations, Finance, Marketing, and Engineering
• Co-facilitate hands-on workshops with internal teams
• Coach peers on prompt engineering, workflow setups, and GenAI tooling
• Test, evaluate, and validate emerging GenAI capabilities and platforms
• Keep the internal technology stack up to date
• Maintain the central AI Experiment Registry
• Track active projects and measure performance
• Standardize successful workflows company-wide
• Report to the AI Transformation Lead

• Perform linguistic project tasks including categorization, annotation, correction, transcription, evaluation, conversational interactions, voice recording, content creation, and localization
• Validate audio, video, images, sentences, or words
• Complete tasks remotely through an online platform available 24/7
• Complete required qualification tests after submitting an application
• Provide documentation or information reasonably requested to verify identity and credentials

Linguistic Projects, Dutch

• Build and maintain SQL models in BigQuery across delivery, procurement, retrieval, and warehouse performance
• Follow layered data modeling conventions
• Develop and iterate on internal dashboards that surface important metrics
• Translate data into decisions during recurring walkthrough sessions with service owners
• Build and refine AI-powered workflows
• Own improvements to the Customer Support AI
• Identify new areas where automation can create leverage
• Analyze operational questions, including SLA performance and carrier and supplier data
• Turn findings into clear recommendations
• Work hands-on with the data warehouse and convert messy operational data into actionable insight

Data & AI Intern, Data Infrastructure, AI-Powered Automations

• Own AI implementation for transaction monitoring alert resolution from identifying manual steps through production deployment
• Understand alert resolution from pickup through false positive, true positive or offboarding
• Build AI-driven investigations of customers, suspicious transactions, behavioural patterns and network patterns
• Build and iterate AI agents with boundaries, escalation logic and audit trails
• Redesign alert resolution around automation, validation and human decision-making
• Define and document the AI/AML boundary for risk management, audit and regulators
• Support and upskill analysts transitioning to model and output validation
• Analyse alert and customer data to identify inefficiencies, false-positive drivers and automation opportunities
• Measure cycle time, alert backlog, AI resolution share, decision quality, analyst capacity and customer impact
• Partner with AI, Data, Engineering, Product and risk management stakeholders
• Maintain customer-focused processes that improve efficiency without degrading customer experience
• Own procedures, decision logic, model rationale and controls to audit standard

AI Process Owner – Transaction Monitoring, Customer Lifecycle

• Own AI implementation for transaction monitoring alert resolution from identifying high-value manual steps through production deployment
• Understand the alert resolution process from pickup through false positive, true positive or offboarding
• Build AI-driven investigations of customers, suspicious transactions, behavioural patterns and network patterns
• Build and iterate AI agents that replace manual analyst work with boundaries, escalation logic and audit trails
• Redesign alert resolution around automation, validation and human decision-making
• Define and document the AI/AML boundary for risk management, audit and regulators
• Support and upskill analysts during the transition to model and output validation
• Analyse alert and customer data to identify inefficiencies, false-positive drivers and automation opportunities
• Measure process changes and their impact
• Partner with AI, Data, Engineering, Product and risk-management stakeholders
• Ensure efficiency improvements do not degrade customer experience
• Own audit-standard procedures, decision logic, model rationale and controls
• Drive reductions in alert handling time and backlog
• Increase AI-resolved or pre-processed alerts while maintaining or improving quality
• Track QA, validation sampling, audit outcomes, analyst capacity and customer-facing impact

• Own AI implementation for transaction monitoring alert resolution from identifying high-value manual steps through production deployment
• Understand the alert resolution process from pickup to false positive, true positive, or offboarding
• Build AI-driven investigation capabilities for customers, suspicious transactions, and behavioural and network patterns
• Build and iterate AI agents that replace manual analyst work with clear boundaries, escalation logic, and audit trails
• Redesign alert resolution around automation, validation, human review, and quality evidence
• Define and document the AI/AML boundary for risk management, audit, and regulators
• Support and upskill analysts transitioning to model and output validation
• Analyse alert and customer data to identify inefficiencies, false-positive drivers, and automation opportunities
• Partner with AI, Data, Engineering, Product, and risk management teams to translate operational and AML needs into technical requirements
• Improve customer experience by reducing unnecessary touchpoints and resolution delays
• Own procedures, decision logic, model rationale, and controls to audit standards
• Track cycle time, alert backlog, AI resolution share, decision quality, analyst capacity, and customer-facing impact

• Provide tactical advisory to ensure the business gets the best value from its portfolio of services and applications
• Act as a platform technical and functional advisor
• Provide consultancy support and share best practices across global business teams
• Represent Arcadis technology colleagues in meetings with vendor enterprise teams
• Collaborate with Arcadis operational teams on adoption, pursuits and project delivery
• Help administer, maintain and enable leverage of project data within common data environments, including effective use of AI
• Create and support knowledge base articles to maintain platform knowledge
• Drive adoption of the best-suited applications and platforms for given tasks
• Manage and renegotiate contracts where applicable
• Support resolution of escalations, feedback and communications
• Act as business partner for designated services
• Collaborate with enabling functions to ensure continuous compliance with Arcadis policies
• Share accountability for business stakeholder and vendor relationships
• Contribute knowledge and best practices across teams within the tower

Artificial Intelligence jobs in Netherlands

AI Enablement Engineer

AI Enablement Engineer

Linguistic Projects, Dutch

Data & AI Intern, Data Infrastructure, AI-Powered Automations

AI Process Owner – Transaction Monitoring, Customer Lifecycle

AI Process Owner – Transaction Monitoring, Customer Lifecycle

AI Process Owner – Transaction Monitoring, Customer Lifecycle

Software Platform Partner II – CDE, AI