Project description

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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.

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 & Git

Ops
Build 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 WAF
Guard

Duty
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
Cloud

Watch 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)
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

Experience & Certifications
4+ years of hands-on AWS experience
AWS 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: xqysrnh
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
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 workloads
OIDC federation: Git

Hub Actions → AWS
EKS OIDC provider integration Observability & Debugging
Familiarity with: Prometheus, Grafana
Open

Telemetry
AWS X-Ray
Cloud

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

Languages
English: B2

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