AI Architect

Metyis is seeking an AI Architect with 3-5 years of experience to join their Data & Analytics team in Amsterdam. The role involves designing and implementing scalable AI solutions, working with cloud infrastructure, data pipelines, and AI applications. The ideal candidate has experience with DevOps, cloud providers, and AI/ML technologies.

HybridFull-timeMid LevelDevOpsCloud Infrastructure

AI Architect

Metyis is seeking an AI Architect with 3-5 years of experience to join their Data & Analytics team in Amsterdam. The role involves designing and implementing scalable AI solutions, working with cloud infrastructure, data pipelines, and AI applications. The ideal candidate has experience with DevOps, cloud providers, and AI/ML technologies.

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HybridFull-timeMid LevelDevOps

Salary

Not specified

Work Location

Amsterdam, North Holland, Netherlands, NL

Work Model

Hybrid

Experience Required

5 years

Employment Type

Full-time

Experience Level

3-5 years of experience

Core Qualifications

Technical (Must-have)

DevOpsCloud InfrastructureData EngineeringIT ArchitectureAI/MLModel ServingData PipelinesVector DatabasesAPIsOrchestration FrameworksAzureAWSGCPInfrastructure-as-CodeCI/CDDockerKubernetesMonitoring ToolsData WarehousesData LakesData Governance

Soft Skills

CommunicationCollaborationProblem SolvingAttention to DetailStructured ApproachOwnershipCuriosity

Preferred Qualifications

Technical (Nice-to-have)

Databricks

Key Responsibilities

•Contribute to the design and implementation of scalable, reliable, and secure technical foundations for AI solutions.
•Work closely with data, IT, and business stakeholders to understand technical requirements and translate them into effective solutions.
•Support the design and implementation of AI applications, data pipelines, and cloud-based solutions, following established architectural principles and best practices.
•Contribute to technical specifications and documentation, follow up on development activities, and support testing and acceptance activities.
•Support the integration, deployment, and scaling of AI systems across relevant technology environments.
•Monitor the performance, reliability, and cost of AI infrastructure and applications, identifying issues and supporting their resolution.
•Participate in technical discussions and project governance forums, clearly communicating technical topics, progress, and potential risks.
•Identify technical challenges and risks during delivery and work with senior team members to develop appropriate solutions and mitigation strategies.
•Continuously develop knowledge of emerging AI, cloud, data, and infrastructure technologies and share relevant learnings with the wider team.

AI ArchitectData & AnalyticsCloud InfrastructureData EngineeringAI/MLAzureAWSGCPDevOpsHybrid