Senior Platform DevOps Engineer

Gorilla Logic

. Manage, operate, and troubleshoot production Kubernetes environments and workloads .

Posted 10/1/2026full-timeRemote • Colombia, Costa RicaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in managing Kubernetes environments and deploying applications using Terraform and GitOps practices. Proficient in Python scripting for automation and operational workflows, with a strong focus on platform reliability and incident resolution.

Highest-signal resume keywords

Kubernetes ManagementTerraform ProficiencyPython ScriptingGitOps PracticesAWS Cloud Infrastructure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Kubernetes DeploymentsInfrastructure as CodeApplication Deployment ManagementProduction Incident TroubleshootingPlatform AutomationKubernetes AutoscalingHelm Package ManagementService-to-Service NetworkingElasticsearchArangoDB

Soft Skills

Problem-SolvingOwnership and AccountabilityCommunicationCollaborationQuality-First Mindset

Tools & Technologies

Argo CDPyTorchHugging Face TransformersNVIDIA Triton Inference ServerChainguardTrivyApache Kafka

Industry Keywords

Production EnvironmentsOperational Best PracticesCloud InfrastructureML Inference PlatformsFedRAMP

Tech Stack

Tools & technologies

ApacheAWSCloudElasticSearchKafkaKubernetesOpenShiftPythonPyTorchTerraform

About the role

Key responsibilities & impact

Manage, operate, and troubleshoot production Kubernetes environments and workloads
Build, maintain, and improve infrastructure using Terraform and Infrastructure as Code practices
Manage application deployments, upgrades, configuration changes, and complex deployment lifecycles
Work with GitOps-based deployment processes and tools such as Argo CD
Develop and maintain Python scripts and tooling for platform automation and operational workflows
Troubleshoot and resolve production incidents across infrastructure, applications, and platform services
Improve platform reliability, scalability, observability, and operational efficiency
Support Kubernetes scaling and autoscaling strategies for production workloads
Collaborate with development and platform teams to resolve infrastructure and deployment challenges
Participate in technical decisions and identify risks, reliability concerns, and improvement opportunities
Maintain high engineering and quality standards, providing technical pushback when necessary
Take ownership of platform initiatives and drive issues through resolution with minimal supervision

Requirements

What you’ll need

Strong hands-on experience managing Kubernetes in production environments
Experience with Kubernetes deployments, scaling, troubleshooting, and operational management
Hands-on experience with Terraform for provisioning and managing cloud infrastructure
Ability to read and write Python for scripting, automation, troubleshooting, and platform tooling
Experience with AWS cloud infrastructure, ideally including EKS or similar managed Kubernetes environments
Experience with GitOps practices and deployment tools such as Argo CD
Experience managing complex application deployment and upgrade lifecycles
Proven experience troubleshooting, triaging, and supporting production incidents
Strong understanding of infrastructure reliability, scalability, and operational best practices
Strong problem-solving skills and the ability to independently investigate complex production issues
Strong sense of ownership and accountability, with the ability to operate effectively with limited supervision
Quality-first mindset with the judgment to balance delivery speed, reliability, and long-term maintainability
Strong communication and collaboration skills
Preferred: Experience with Helm and Kubernetes package/deployment management
Preferred: Familiarity with PyTorch and Hugging Face Transformers
Preferred: Experience supporting GPU-based workloads or ML inference platforms
Preferred: Familiarity with NVIDIA Triton Inference Server
Preferred: Experience with Chainguard, distroless container images, Trivy, or container vulnerability reduction
Preferred: Experience implementing or improving Kubernetes autoscaling solutions
Preferred: Familiarity with streaming or messaging platforms such as Apache Kafka or similar technologies
Preferred: Experience with Elasticsearch or ArangoDB
Preferred: Experience troubleshooting complex service-to-service networking
Preferred: Exposure to OpenShift, IL5, FedRAMP, or similarly constrained environments
Preferred: Familiarity with AI/ML or agentic AI development environments

Benefits

Comp & perks

Remote work arrangement
Full-time employment