Cloud Platform Engineer (Agentic AI) Luxoft Spain•Tarragona, tarragonés (comarca); provincia de tarragona; cataluña, Spain

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.

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

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 https://jobeax.com/link/JSd7UYCSg572jJDY
FinOps experience:
AWS Cost Explorer
Compute Optimizer
Tagging governance
Savings Plan management

Languages

English: B2

Cloud Platform Engineer (Agentic Ai)

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