Project description

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.

ResponsibilitiesAWS Infrastructure & Architecture

Design, provision, and manage AWS infrastructure using Terraform, aligned with the AWS Well-Architected Framework

Core services include: Amazon EKSVPCIAMApplication Load Balancer (ALB)Route 53AWS 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 upgradesIRSA (IAM Roles for Service Accounts) configuration

Multi-AZ high availability and resilienceCI/CD & Git

OpsBuild and maintain automated deployment pipelines using: Git

Hub Actions

ArgoCD (Git

Ops)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 WAFGuard

Duty

Security HubKMS (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

Cloud

Watch Container InsightsAWS X-Ray (distributed tracing)AI/ML Integration

Leverage AWS AI/ML services to support agent orchestration:



Amazon Bedrock (model inference, agent APIs)Sage

Maker (model hosting, endpoints)Comprehend (NLP, PII detection)Cost Optimization (Fin

Ops)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

Experience & Certifications4+ years of hands-on AWS experienceAWS Certifications: Required: AWS Solutions Architect (Associate or Professional)Preferred: Dev

Ops 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, ACMIAM, KMS, Secrets ManagerIAM Identity Center

Cloud

Trail, AWS Config

Guard

Duty, Security Hub, AWS WAF AI/ML Exposure

Practical experience with: Amazon Bedrock (model invocation, agent APIs)Sage

Maker (model deployment and endpoints)Comprehend (NLP and PII detection) Dev

Ops & Identity

Experience with: Git

Ops tools (ArgoCD or Flux)CI/CD pipelines for container workloadsOIDC federation: Git

Hub Actions AWSEKS OIDC provider integration Observability & Debugging

Familiarity with: Prometheus, Grafana

Open

TelemetryAWS X-Ray

Cloud

Watch Logs Insights Kubernetes Security

Strong understanding of: Pod Security Standards

Network Policies

Admission webhooks

Service account least-privilege principles

📌 Cloud Platform Engineer (Agentic AI) (España)
🏢 Luxoft
📍 España