Sr. Platform Engineer-Hybrid

Sr. Platform Engineer

Location: Seattle based, client hybrid working is needed - 3 days office in Seattle, WA. Visa: Any visa is ok.

Skills needed:

• Data dog
• New Relic
• Kubernetes Administration – AKS
• Hands-on with setting up Kubernetes clusters for containerized applications
• Scripting – PowerShell / Python
• Very strong with Terraform/setting up Terraform AI/ML platforms
• Note – This is a platform engineer role and not SRE or DevOps role. Role of platform engineer is different from SRE and DevOps.
• Platform engineer will:
• Set up Kubernetes clusters – need a very strong candidate on this
• Set up AKS environment
• Set up monitoring tools like Data Dog/Splunk/New Relic etc
• Client is heavy on Azure cloud so that is very critical for this role
• Some experience in Adobe Integration is good to have

Platform Engineer responsibilities:

1. Design, deploy, and manage infrastructure solutions using Terraform, ensuring scalability, security, and reliability.
2. Develop and maintain infrastructure as code scripts to automate the provisioning and configuration of resources.
3. Implement and manage Kubernetes clusters for containerized applications.
4. Collaborate with development teams to deploy, scale, and optimize applications in Kubernetes environments.
5. Leverage scripting languages (e.g. Python) to automate routine tasks and streamline workflows.
6. Implement continuous integration and continuous deployment (CI/CD) pipelines for efficient software delivery.
7. Ensure seamless integration of infrastructure components with CI/CD pipelines.
8. Design, deploy, and maintain scalable and reliable infrastructure for AI/ML platforms.
9. Implement containerization (Docker) and orchestration (Kubernetes) solutions for deploying and managing AI/ML applications.
10. Ensure containerized applications are secure, scalable, and easily deployable.
11. Enable seamless integration of AI/ML models into the platform, ensuring data pipelines are efficient and reliable.
12. Establish monitoring and alerting systems to ensure the health and performance of AI/ML platforms.
13. Implement security best practices for AI/ML platforms, ensuring data privacy and compliance with industry standards