Project description The project is for one of the worlds 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.

Responsibilities AWS Infrastructure & Architecture. Design, provision, and manage AWS infrastructure using Terraform, aligned with the AWS Well-Architected Framework.

Core services include: Amazon EKS VPC IAM Application Load Balancer (ALB) Route 53 AWS Certificate Manager (ACM) Kubernetes (EKS) Platform Operations Own and operate EKS clusters end-to-end

Managed node group lifecycle management: Karpenter-based autoscaling Cluster add-on lifecycle upgrades IRSA (IAM Roles for Service Accounts) configuration Multi-AZ high availability and resilience CI/CD & GitOps

Build and maintain automated deployment pipelines using: GitHub Actions ArgoCD (GitOps)

Enable multi-environment deployments: Dev → QA → Production

Implement release strategies: Blue/Green deployments Canary releases Security & Compliance

Integrate AWS-native security and governance controls: AWS WAF GuardDuty Security Hub KMS (encryption) Secrets Manager External Secrets Operator

Enforce policy controls using:



OPA / Kyverno (admission controllers) Observability & Monitoring

Implement and manage observability stack: Amazon Managed Prometheus Amazon Managed Grafana CloudWatch Container Insights AWS X-Ray (distributed tracing) AI/ML Integration

Leverage AWS AI/ML services to support agent orchestration: Amazon Bedrock (model inference, agent APIs) SageMaker (model hosting, endpoints) Comprehend (NLP, PII detection) Cost Optimization (FinOps)

Implement cost-efficient architecture practices: Spot Instances Savings Plans Karpenter bin-packing strategies Scheduled scale-to-zero for non-production environments Platform & Engineering Collaboration

Partner with platform and ML teams to: Onboard new AI agent workloads Integrate MCP servers and execution frameworks Support extensibility of the agent ecosystem

Skills Must have 4+ years of hands-on AWS experience

AWS Certifications: Required: AWS Solutions Architect (Associate or Professional) Preferred: DevOps Engineer, Security Specialty Kubernetes & EKS Expertise

Strong hands-on experience with: EKS cluster provisioning and operations Managed node groups and Karpenter Helm chart management Kubernetes RBAC and network policies Infrastructure as Code (Terraform)





Advanced Terraform capabilities: Modular design Remote state management (S3 + DynamoDB) Multi-environment configuration Security scanning (Checkov, tfsec) AWS Services Proficiency

Deep knowledge of: EKS, ECR, ALB, Route 53, ACM IAM, KMS, Secrets Manager IAM Identity Center CloudTrail, AWS Config GuardDuty, Security Hub, AWS WAF AI/ML Exposure

Practical experience with: Amazon Bedrock (model invocation, agent APIs) SageMaker (model deployment and endpoints) Comprehend (NLP and PII detection) DevOps & Identity

Experience with: GitOps tools (ArgoCD or Flux) CI/CD pipelines for container workloads

OIDC federation: GitHub Actions → AWS EKS OIDC provider integration Observability & Debugging

Familiarity with: Prometheus, Grafana OpenTelemetry AWS X-Ray CloudWatch Logs Insights Kubernetes Security

Strong understanding of: Pod Security Standards Network Policies Admission webhooks Service account least-privilege principles

Nice to have Experience with AI agent frameworks: LangChain, Claude Agent SDK, or similar

Knowledge of emerging protocols: A2A (Agent-to-Agent) MCP (Model Context Protocol)

Familiarity with: Amazon Bedrock Agents, Knowledge Bases, Guardrails

Chaos engineering exposure: AWS Fault Injection Service (FIS)

Multi-tenant platform design: Namespace isolation Self-service provisioning

Programming/debugging skills: Python, Go, or Node.js

FinOps experience: AWS Cost Explorer Compute Optimizer Tagging governance Savings Plan management

Languages English: B2

📌 Cloud Platform Engineer (Agentic AI) (Madrid)
🏢 Luxoft Spain
📍 Madrid