Platform Engineer (DevOps)

Cyber Sphere LLC
2 days ago

Role details

Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior

Job location

Remote

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Application Layers
Continuous Integration
DevOps
Distributed Systems
Github
Identity and Access Management
Networking Basics
Runbook
Scripting (Bash/Python/Go/Ruby)
Istio
Delivery Pipeline
Gitlab
Cloudformation
Containerization
Kubernetes
Terraform
Jenkins

Job description

We re looking for a hands-on junior platform engineer to support a cloud-native environment with a strong DevOps/automation mindset. The ideal candidate has experience working in AWS, supporting containerized workloads, and building reliable delivery pipelines. This role will partner across infrastructure and application layers to improve deployment workflows, observability, and operational reliability., * Supporting CI/CD pipelines and improving deployment reliability

  • Automating operational tasks and reducing toil (scripts, runbooks, self-service)
  • Helping maintain and monitor cloud/container environments (AWS + Kubernetes/EKS where needed)
  • Partnering with engineers on troubleshooting production issues and improving observability
  • Contributing to IaC and platform documentation/standards

Requirements

  • 1 3+ years in DevOps / platform / SRE-adjacent work (flexible)
  • Experience with AWS (any mix of ECS/EKS, EC2, IAM, networking basics)
  • Working knowledge of containers + Kubernetes concepts (hands-on preferred)
  • Experience with Infrastructure as Code (Terraform preferred; CloudFormation ok)
  • CI/CD experience (GitHub Actions/Jenkins/GitLab, etc.) and scripting/automation
  • Comfortable troubleshooting across distributed systems with good communication + follow-through

Nice to have

  • Hands-on EKS experience
  • Service mesh exposure (Istio or similar)
  • AI/automation experience (using AI to accelerate troubleshooting, scripts, runbooks, or pipeline improvements)

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