Gorilla Logic
Gorilla Logic
501 – 1,000 Employees
ConsultingLogisticsMarketing
Gorilla Logic is a software and data engineering consulting company that helps organizations design, build, and modernize digital products. Its work spans digital product design, cloud engineering, data and AI, DevOps, quality assurance, legacy modernization, and SaaS development. The company brings together product designers, solutions architects, and Agile nearshore engineering teams to support business-critical applications for Fortune 500 companies and small and midsize businesses. With teams in Costa Rica, Colombia, Mexico, and the United States, Gorilla Logic works through collaborative, security-focused partnerships across the full digital product lifecycle.

Senior Platform DevOps Engineer (Remote)

Join Gorilla Logic as a senior DevOps engineer supporting AWS and Kubernetes production platforms. Automate infrastructure, deployments, reliability, and production operations for teams working remotely from Colombia or Costa Rica.

Description

  • Operate and troubleshoot production Kubernetes clusters and workloads
  • Provision and enhance cloud infrastructure with Terraform and Infrastructure as Code practices
  • Oversee application deployments, upgrades, configuration updates, and complex release lifecycles
  • Use GitOps workflows and tools such as Argo CD to manage deployments
  • Create and maintain Python scripts and tools for platform automation and operational processes
  • Investigate and resolve incidents involving infrastructure, applications, and platform services
  • Strengthen platform reliability, scalability, observability, and operational efficiency
  • Support scaling and autoscaling strategies for production Kubernetes workloads
  • Partner with development and platform teams to address infrastructure and deployment issues
  • Contribute to technical decisions while identifying risks, reliability gaps, and improvement areas
  • Uphold high engineering and quality standards, offering constructive technical challenge when needed
  • Own platform initiatives and carry issues through resolution with limited supervision

Requirements

  • Demonstrated hands-on experience operating Kubernetes in production
  • Experience deploying, scaling, troubleshooting, and administering Kubernetes workloads
  • Practical Terraform experience for provisioning and managing cloud infrastructure
  • Ability to read and write Python for scripting, automation, troubleshooting, and platform tooling
  • Experience with AWS infrastructure, preferably including EKS or a comparable managed Kubernetes service
  • Experience applying GitOps practices with tools such as Argo CD
  • Background managing complex application deployment and upgrade lifecycles
  • Proven ability to triage, troubleshoot, and support production incidents
  • Strong knowledge of infrastructure reliability, scalability, and operational best practices
  • Strong analytical skills and independence when investigating complex production problems
  • High ownership and accountability, with the ability to work effectively with limited supervision
  • Quality-focused judgment when balancing delivery speed, reliability, and maintainability
  • Strong written and verbal communication and collaboration skills
  • Preferred: Experience with Helm and Kubernetes package or deployment management
  • Preferred: Familiarity with PyTorch and Hugging Face Transformers
  • Preferred: Experience supporting GPU workloads or machine learning inference platforms
  • Preferred: Familiarity with NVIDIA Triton Inference Server
  • Preferred: Experience with Chainguard, distroless images, Trivy, or reducing container vulnerabilities
  • Preferred: Experience implementing or improving Kubernetes autoscaling
  • Preferred: Familiarity with Apache Kafka or comparable streaming and messaging systems
  • Preferred: Experience with Elasticsearch or ArangoDB
  • Preferred: Experience troubleshooting complex service-to-service networking
  • Preferred: Exposure to OpenShift, IL5, FedRAMP, or similarly restricted environments
  • Preferred: Familiarity with AI/ML or agentic AI development environments

Benefits

  • Remote work arrangement
  • Full-time employment

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