The project is for one of the world's famous science and technology companies in pharmaceutical industry, supporting initiatives in AWS, AI and data engineering, with plans to launch over 20 additional initiatives in the future.We are seeking a highly skilled Cloud Engineer to lead the infrastructure design, deployment, and operations of the AI agent orchestration platform on AWS. This role is responsible for building and managing a Kubernetes-native, enterprise-grade platform that supports scalable AI agent workloads across development, QA, and production environments.ResponsibilitiesDesign, provision, and manage AWS infrastructure using Terraform, aligned with the AWS Well-Architected Framework.Core services include:Amazon EKSVPCIAMRoute 53Own and operate EKS clusters end-to-endManaged node group lifecycle management:Karpenter-based autoscalingCluster add-on lifecycle upgradesIRSA (IAM Roles for Service Accounts) configurationMulti-AZ high availability and resilienceCI/CD & GitOpsBuild and maintain automated deployment pipelines using:GitHub ActionsArgoCD (GitOps)Implement release strategies:Canary releasesSecurity & ComplianceIntegrate AWS-native security and governance controls:AWS WAFGuardDutySecurity HubKMS (encryption)Secrets ManagerExternal Secrets OperatorEnforce policy controls using:Observability & MonitoringImplement and manage observability stack:Amazon Managed PrometheusAmazon Managed GrafanaCloudWatch Container InsightsAWS X‑Ray (distributed tracing)AI/ML IntegrationLeverage AWS AI/ML services to support agent orchestration:Cost Optimization (FinOps)Spot InstancesSavings PlansKarpenter bin‑packing strategiesScheduled scale‑to‑zero for non‑production environmentsPlatform & Engineering CollaborationPartner with platform and ML teams to:Integrate MCP servers and execution frameworksSupport extensibility of the agent ecosystemSkillsMust have4+ years of hands‑on AWS experienceAWS Certifications:Required: AWS Solutions Architect (Associate or Professional)Preferred: DevOps Engineer, Security Specialty Kubernetes & EKS ExpertiseStrong hands‑on experience with:EKS cluster provisioning and operationsManaged node groups and KarpenterKubernetes RBAC and network policies Infrastructure as Code (Terraform)Advanced Terraform capabilities:Remote state management (S3 + DynamoDB)Security scanning (Checkov, tfsec) AWS Services ProficiencyDeep knowledge of:EKS, ECR, ALB, Route 53, ACMIAM, KMS, Secrets ManagerIAM Identity CenterCloudTrail, AWS ConfigGuardDuty, Security Hub, AWS WAF AI/ML ExposurePractical experience with:SageMaker (model deployment and endpoints)Comprehend (NLP and PII detection) DevOps & IdentityExperience with:GitOps tools (ArgoCD or Flux)CI/CD pipelines for container workloadsGitHub Actions → AWSEKS OIDC provider integration Observability & DebuggingFamiliarity with:OpenTelemetryAWS X‑RayStrong understanding of:Pod Security StandardsAdmission webhooksService account least‑privilege principlesNice to haveExperience with AI agent frameworks:LangChain, Claude Agent SDK, or similarKnowledge of emerging protocols:A2A (Agent‑to‑Agent)Familiarity with:Amazon Bedrock Agents, Knowledge Bases, GuardrailsNamespace isolationProgramming/debugging skills:Python, Go, or Node.JsAWS Cost ExplorerLanguagesGKEAlloyDBHoyThe project is for one of the world's famous science and technology companies in pharmaceutical industry, supporting initiatives in AWS, AI and data engineering,



with plans to launch over 20 additional initiatives in the future.We are seeking a highly skilled Cloud Engineer to lead the infrastructure design, deployment, and operations of the AI agent orchestration platform on AWS. This role is responsible for building and managing a Kubernetes-native, enterprise-grade platform that supports scalable AI agent workloads across development, QA, and production environments.ResponsibilitiesDesign, provision, and manage AWS infrastructure using Terraform, aligned with the AWS Well-Architected Framework.Core services include:Amazon EKSVPCIAMRoute 53Own and operate EKS clusters end-to‑endManaged node group lifecycle management:Karpenter-based autoscalingCluster add‑on lifecycle upgradesIRSA (IAM Roles for Service Accounts) configurationMulti‑AZ high availability and resilienceCI/CD & GitOpsBuild and maintain automated deployment pipelines using:GitHub ActionsArgoCD (GitOps)Implement release strategies:Canary releasesSecurity & ComplianceIntegrate AWS-native security and governance controls:AWS WAFGuardDutySecurity HubKMS (encryption)Secrets ManagerExternal Secrets OperatorEnforce policy controls using:Observability & MonitoringImplement and manage observability stack:Amazon Managed PrometheusAmazon Managed GrafanaCloudWatch Container InsightsAWS X‑Ray (distributed tracing)AI/ML IntegrationLeverage AWS AI/ML services to support agent orchestration:Cost Optimization (FinOps)Spot InstancesSavings PlansKarpenter bin‑packing strategiesScheduled scale‑to‑zero for non‑production environmentsPlatform & Engineering CollaborationPartner with platform and ML teams to:Integrate MCP servers and execution frameworksSupport extensibility of the agent ecosystemSkillsMust have4+ years of hands‑on AWS experienceAWS Certifications:Required: AWS Solutions Architect (Associate or Professional)Preferred: DevOps Engineer, Security Specialty Kubernetes & EKS ExpertiseStrong hands‑on experience with:EKS cluster provisioning and operationsManaged node groups and KarpenterKubernetes RBAC and network policies Infrastructure as Code (Terraform)Advanced Terraform capabilities:Remote state management (S3 + DynamoDB)Security scanning (Checkov, tfsec) AWS Services ProficiencyDeep knowledge of:EKS, ECR, ALB, Route 53, ACMIAM, KMS, Secrets ManagerIAM Identity CenterCloudTrail, AWS ConfigGuardDuty, Security Hub, AWS WAF AI/ML ExposurePractical experience with:SageMaker (model deployment and endpoints)Comprehend (NLP and PII detection) DevOps & IdentityExperience with:GitOps tools (ArgoCD or Flux)CI/CD pipelines for container workloadsGitHub Actions → AWSEKS OIDC provider integration Observability & DebuggingFamiliarity with:OpenTelemetryAWS X‑RayStrong understanding of:Pod Security StandardsAdmission webhooksService account least‑privilege principlesNice to haveExperience with AI agent frameworks:LangChain, Claude Agent SDK, or similarKnowledge of emerging protocols:A2A (Agent‑to‑Agent)Familiarity with:Amazon Bedrock Agents, Knowledge Bases,



GuardrailsNamespace isolationProgramming/debugging skills:Python, Go, or Node.JsAWS Cost ExplorerLanguagesGKEAlloyDBHoyThe project is for one of the world's famous science and technology companies in pharmaceutical industry, supporting initiatives in AWS, AI and data engineering, with plans to launch over 20 additional initiatives in the future.We are seeking a highly skilled Cloud Engineer to lead the infrastructure design, deployment, and operations of the AI agent orchestration platform on AWS. This role is responsible for building and managing a Kubernetes-native, enterprise-grade platform that supports scalable AI agent workloads across development, QA, and production environments.ResponsibilitiesDesign, provision, and manage AWS infrastructure using Terraform, aligned with the AWS Well-Architected Framework.Core services include:Amazon EKSVPCIAMRoute 53Own and operate EKS clusters end-to‑endManaged node group lifecycle management:Karpenter-based autoscalingCluster add‑on lifecycle upgradesIRSA (IAM Roles for Service Accounts) configurationMulti‑AZ high availability and resilienceCI/CD & GitOpsBuild and maintain automated deployment pipelines using:GitHub ActionsArgoCD (GitOps)Implement release strategies:Canary releasesSecurity & ComplianceIntegrate AWS-native security and governance controls:AWS WAFGuardDutySecurity HubKMS (encryption)Secrets ManagerExternal Secrets OperatorEnforce policy controls using:Observability & MonitoringImplement and manage observability stack:Amazon Managed PrometheusAmazon Managed GrafanaCloudWatch Container InsightsAWS X‑Ray (distributed tracing)AI/ML IntegrationLeverage AWS AI/ML services to support agent orchestration:Cost Optimization (FinOps)Spot InstancesSavings PlansKarpenter bin‑packing strategiesScheduled scale‑to‑zero for non‑production environmentsPlatform & Engineering CollaborationPartner with platform and ML teams to:Integrate MCP servers and execution frameworksSupport extensibility of the agent ecosystemSkillsMust have4+ years of hands‑on AWS experienceAWS Certifications:Required: AWS Solutions Architect (Associate or Professional)Preferred: DevOps Engineer, Security Specialty Kubernetes & EKS ExpertiseStrong hands‑on experience with:EKS cluster provisioning and operationsManaged node groups and KarpenterKubernetes RBAC and network policies Infrastructure as Code (Terraform)Advanced Terraform capabilities:Remote state management (S3 + DynamoDB)Security scanning (Checkov, tfsec) AWS Services ProficiencyDeep knowledge of:EKS, ECR, ALB, Route 53, ACMIAM, KMS, Secrets ManagerIAM Identity CenterCloudTrail, AWS ConfigGuardDuty, Security Hub, AWS WAF AI/ML ExposurePractical experience with:SageMaker (model deployment and endpoints)Comprehend (NLP and PII detection) DevOps & IdentityExperience with:GitOps tools (ArgoCD or Flux)CI/CD pipelines for container workloadsGitHub Actions → AWSEKS OIDC provider integration Observability & DebuggingFamiliarity with:OpenTelemetryAWS X‑RayStrong understanding of:Pod Security StandardsAdmission webhooksService account least‑privilege principlesNice to haveExperience with AI agent frameworks:LangChain, Claude Agent SDK, or similarKnowledge of emerging protocols:A2A (Agent‑to‑Agent)Familiarity with:Amazon Bedrock Agents, Knowledge Bases, GuardrailsNamespace isolationProgramming/debugging skills:Python, Go, or Node.JsAWS Cost ExplorerLanguagesGKEAlloyDBHoyGKEAlloyDB#J-18808-Ljbffr

📌 Cloud Platform Engineer (Agentic Ai) (Valladolid)
🏢 Luxoft Spain
📍 Valladolid