Platform Engineer II

• *Job Summary**
• --------------

We are looking for an AI Engineer II (E2\) to support the deployment, operation, and optimization of cloud\-native infrastructure for AI and enterprise applications. The role focuses on implementing and maintaining Kubernetes\-based platforms, automating operational tasks, supporting CI/CD processes, and assisting in ensuring the reliability, scalability, and security of cloud environments.

The ideal candidate should have hands\-on experience with Kubernetes, Docker, cloud platforms (AWS/Azure/GCP), Infrastructure as Code, and DevOps practices. Working under the guidance of senior engineers, you will contribute to platform operations, monitoring, troubleshooting, automation, and continuous improvement initiatives.

• *Key Responsibilities**
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• Support the operation and maintenance of Kubernetes clusters (EKS/AKS/GKE/OpenShift) and AI platform workloads.
• Assist in deploying and managing applications using Helm charts across development, testing, and production environments.
• Support workload identity, secrets management, and access control using cloud\-native services and enterprise standards.
• Assist in configuring and troubleshooting Kubernetes networking, ingress controllers, load balancers, DNS, and TLS certificates.
• Support storage management using CSI drivers, StorageClasses, and Persistent Volume Claims (PVCs).
• Contribute to Infrastructure as Code implementations using Terraform for cloud and platform resources.
• Assist in building and maintaining CI/CD pipelines for application deployment and operational automation.
• Follow established security and compliance standards, including RBAC, least\-privilege access, and container security best practices.
• Monitor platform health, performance, logging, and alerting systems; assist in incident response and troubleshooting.
• Provide operational support for platform services such as PostgreSQL, OpenSearch, and identity management solutions.
• Document deployment procedures, troubleshooting guides, and operational runbooks.
• Collaborate with engineering, platform, and delivery teams to support customer and business requirements.
• Participate in automation and continuous improvement initiatives to enhance platform reliability and operational efficiency.

• *Skill Requirements**
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• *Containers \& Orchestration**

• Working experience with Docker and containerized applications.
• Hands\-on experience with Kubernetes (EKS/AKS/GKE/OpenShift).
• Basic to intermediate experience with Helm chart deployments and configuration management.

• *Cloud Platforms**

• Hands\-on experience with at least one cloud platform (AWS, Azure, or GCP).
• Understanding of cloud networking, IAM, storage, load balancing, and managed services.

• *Kubernetes Platform Fundamentals**

• Understanding of Kubernetes networking concepts, ingress, DNS, and TLS.
• Familiarity with StorageClasses, CSI drivers, and Persistent Volumes.
• Knowledge of RBAC, secrets management, and Kubernetes security fundamentals.

• *Infrastructure as Code**

• Experience working with Terraform to provision and manage cloud resources.

• *CI/CD**

• Experience with GitHub Actions, GitLab CI, Jenkins, or Azure DevOps.
• Understanding of automated build and deployment practices.

• *Scripting \& Operating Systems**

• Basic proficiency in Python and Bash scripting.
• Linux administration and troubleshooting skills.

• *Source Control**

• Experience with Git and modern source\-control workflows.

• *Must Have Skill**
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Devops,Docker,Kubernetes

• *Good to Have Skill**
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• *Other Requirements**
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• *Preferred Skills**

• Exposure to multiple cloud platforms (AWS, Azure, GCP).
• Experience with OpenShift environments.
• Familiarity with monitoring tools such as Prometheus and Grafana.
• Exposure to service mesh technologies such as Istio or Linkerd.
• Understanding of DevSecOps practices, vulnerability management, and container security.
• Knowledge of Keycloak, OIDC, API gateways, or authentication platforms.
• Awareness of cloud cost optimization and FinOps principles.
• Experience supporting AI/ML or Generative AI workloads in cloud environments.

• *Expected Outcomes**

• Successfully support cloud and Kubernetes platform operations.
• Participate in infrastructure deployment and automation initiatives.
• Resolve operational issues with guidance from senior engineers.
• Maintain reliable, secure, and scalable cloud environments.
• Build technical expertise and progress toward independently owning platform components and projects.