Cloud Platform Engineer
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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.
Experiencia, cualificaciones y habilidades interpersonales, ¿tiene todo lo necesario para triunfar en esta oportunidad? Descúbralo a continuación.
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 + D
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