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Cloud Platform Engineer (Agentic AI)
Successfully
Req. VR-123711
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.
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
Must have
Experience & Certifications
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
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 Upper Intermediate
Seniority
Senior
Bengaluru, India
Req. VR-123711
DevOps
Cross Industry Solutions
26/06/2026
Req. VR-123711
Apply for Cloud Platform Engineer (Agentic AI) in Bengaluru
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