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Audacy, Inc. · 20 hours ago

Senior Platform Engineer - GCP

United States

Full-time

Remote

Mid, Senior Level

$140K/yr - $150K/yr

3+ years exp

Audacy is looking for a self-starting and results-oriented Senior Platform Engineer in GCP with a pragmatic and intelligent approach to problem solving. The role involves designing, developing, and supporting applications that deliver streaming broadcast radio and podcasts, while promoting a DevOps culture for developer teams.

Broadcast Media

Responsibilities

Deploy infrastructure to GCP using Terraform & Terragrunt

Support hundreds of deployments over 10+ EKS clusters and 2+ GKE clusters

Provide expert level support to a streaming platform for broadcast radio and Data Team leveraging AI tools like Big Query, Vertex AI, Jupyter Notebook, etc

Work with developer teams to automate their release pipelines using GitLab and empowering them to own the deployment lifecycle

Contribute to project planning and influence solution architecture design that satisfies business goals while maintaining Platform Engineering standards

Deliver 24/7 on-call rotational support of applications and infrastructure

Monitor system and application performance and troubleshoot/resolve escalated issues

Cross functional collaboration in the care and feeding of existing Kubernetes architecture like controller, cluster, and add-on upgrades

Continually identify opportunities to optimize and improve all operational aspects of our technical solutions

Qualification

GCP servicesKubernetes managementTerraformGitLab automationPythonDevOps experienceInfrastructure as codeMonitoring solutionsCollaboration skillsProblem solving

Required

At least 3 years of experience in a DevOps or Platform Engineering role

Proficient experience around pipeline automation with GitLab and automation with Helm like pre-deploy hooks will be helpful

Practical experience with most core GCP services: BigQuery, Vertex AI, Juniper Notebooks, Airflow, Google Transfer Services, Cloud Run, Cloud Storage, Cloud Spanner, etc

Proven experience deploying and supporting GCP services: BigQuery, VertexAI, GKE, Kubeflow pipelines, Networking, etc

Exposure to multiple cloud accounts that leverage VPC peering and Transit Gateway for systems that span cross-account

Hands-on experience managing Kubernetes in a production setting

Demonstrated experience with GitLab, Bitbucket, or GitHub automation

Experience writing infrastructure as code in Terraform

Experience with logging, monitoring, and alerting solutions like Grafana, DataDog, Honeycomb, etc

Practical experience with Python or Go, Ansible and bash

Experience with Unix / Red Hat

Experience troubleshooting and resolving front-end application performance, connectivity, and other issues in a production setting

Demonstrate strong knowledge of engineering cloud based solutions that are fault tolerant and highly available in a production setting

Preferred

At least 3 years of experience with GitLab pipelines and managing runners

Knowledge / familiarity with GCP services like BigQuery, VertexAI, GKE, Kubeflow pipelines, Networking, etc

Experience working with Confluent Cloud and managing clusters/Kafka topics

Experience automating pipelines for language learning models in Google Cloud

Experience using Grafana Alloy in both contexts of EC2 and Kubernetes. You also have experience working with core integrations like Fleet Manager and Open Telemetry

AWS, GCP Certifications