Cloud Platform Engineer (Agentic Ai)

Cloud Platform Engineer (Agentic AI) Luxoft Spain•Castro, Carballedo, carballedo, lugo; chantada (comarca); provincia de lugo; galicia, Spain

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Descripción del trabajo

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.

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) xqbhyrx

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

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