1 day ago

Senior Cloud Architect, Delivery (GenAI)

Jobgether

Netherlands

1 day ago

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Senior Cloud Architect, Delivery (GenAI) position with a partner company, based in Netherlands. The role focuses on designing and delivering production-grade AI and ML solutions at scale, acting as a trusted technical advisor for enterprise customers. Requires 4+ years of cloud-based AI/ML experience, strong AWS expertise, and a customer-facing delivery mindset.

AIHybridFull-timeSeniorAWSAmazon Bedrock

Senior Cloud Architect, Delivery (GenAI)

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AIHybridFull-timeSeniorAWS

Salary

Not specified

Work Location

Netherlands, NL

Work Model

Hybrid

Experience Required

4 years

Employment Type

Full-time

Experience Level

Senior

Core Qualifications

Technical (Must-have)

AWSAmazon BedrockAmazon SageMakerAI/ML SystemsGenAIMLOpsCI/CDInfrastructure-as-CodeData EngineeringDistributed ArchitecturesRAGAgentic SystemsModel EvaluationInference OptimizationDevOps

Soft Skills

CommunicationConsulting MindsetCustomer EngagementTechnical AdvisoryComplex Problem Solving

Preferred Qualifications

Technical (Nice-to-have)

Google CloudMicrosoft AzureAI Governance

Key Responsibilities

•Own the design, delivery and optimization of advanced cloud and GenAI solutions across enterprise customer environments, ensuring scalability, reliability and business value.
•Lead end-to-end architecture and implementation of AI/ML and GenAI workloads on cloud platforms such as Amazon Web Services, with awareness of multi-cloud environments including Google Cloud and Microsoft Azure.
•Design production-grade solutions using services such as Amazon Bedrock and Amazon SageMaker, including deployment, scaling and monitoring of ML systems.
•Translate business and operational challenges into robust cloud architectures focused on cost efficiency, security, performance and resilience.
•Deliver structured technical engagements such as architecture reviews, optimization workshops, and well-architected assessments.
•Act as a senior technical advisor for customers, supporting incident resolution, deep-dive investigations and expert engineering inquiries.
•Collaborate with account teams and customer stakeholders to drive adoption, improve cloud maturity and reduce operational complexity.
•Develop reusable frameworks, automation assets and "golden path" patterns to scale successful solutions across customers.
•Contribute insights back into product and engineering teams to improve platform capabilities and customer experience.

Senior Cloud ArchitectGenAIAWSAI/MLCustomer-facingRemoteNetherlandsFull-time

Core Qualifications

Technical (Must-have)

AWSAmazon BedrockAmazon SageMakerAI/ML SystemsGenAIMLOpsCI/CDInfrastructure-as-CodeData EngineeringDistributed ArchitecturesRAGAgentic SystemsModel EvaluationInference OptimizationDevOps

Soft Skills

CommunicationConsulting MindsetCustomer EngagementTechnical AdvisoryComplex Problem Solving

Key Responsibilities

•Own the design, delivery and optimization of advanced cloud and GenAI solutions across enterprise customer environments, ensuring scalability, reliability and business value.

•Lead end-to-end architecture and implementation of AI/ML and GenAI workloads on cloud platforms such as Amazon Web Services, with awareness of multi-cloud environments including Google Cloud and Microsoft Azure.

•Design production-grade solutions using services such as Amazon Bedrock and Amazon SageMaker, including deployment, scaling and monitoring of ML systems.

•Translate business and operational challenges into robust cloud architectures focused on cost efficiency, security, performance and resilience.

•Deliver structured technical engagements such as architecture reviews, optimization workshops, and well-architected assessments.

•Act as a senior technical advisor for customers, supporting incident resolution, deep-dive investigations and expert engineering inquiries.

•Collaborate with account teams and customer stakeholders to drive adoption, improve cloud maturity and reduce operational complexity.

•Develop reusable frameworks, automation assets and "golden path" patterns to scale successful solutions across customers.

•Contribute insights back into product and engineering teams to improve platform capabilities and customer experience.