What are the responsibilities and job description for the Sr. Platform Engineer( NOT NOT SRE or Devops role.) position at Fortune Global Solutions, LLC?
Job Details
Job Title: Sr. Platform Engineer
Location: Seattle, WA
Duration: Long Term
Note This is a platform engineer role and NOT 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
- Will set up AKS environment
- Will 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
Required:
- Adobe Integration experience
- Data dog
- New relic
- Kubernetes Administration AKS
- Hands on with Setting up Kubernetes clusters
- Kubernetes clusters for containerized applications.
- Scripting PowerShell / Python
- Very strong with Terraform/ setting up terraform
- AI/ML platforms.
Platform Engineer
- Design, deploy, and manage infrastructure solutions using Terraform, ensuring scalability, security, and reliability.
- Develop and maintain infrastructure as code scripts to automate the provisioning and configuration of resources.
- Implement and manage Kubernetes clusters for containerized applications.
- Collaborate with development teams to deploy, scale, and optimize applications in Kubernetes environments.
- Leverage scripting languages (e.g Python) to automate routine tasks and streamline workflows.
- Implement continuous integration and continuous deployment (CI/CD) pipelines for efficient software delivery.
- Ensure seamless integration of infrastructure components with CI/CD pipelines.
- Design, deploy, and maintain scalable and reliable infrastructure for AI/ML platforms.
- Implement containerization (Docker) and orchestration (Kubernetes) solutions for deploying and managing AI/ML applications.
- Ensure containerized applications are secure, scalable, and easily deployable.
- Enable seamless integration of AI/ML models into the platform, ensuring data pipelines are efficient and reliable.
- Establish monitoring and alerting systems to ensure the health and performance of AI/ML platforms.
- Implement security best practices for AI/ML platforms, ensuring data privacy and compliance with industry standards
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