Senior Platform Engineer

securityjourney

North Carolina

Remote

USD 140,000 - 190,000

Full time

14 days+
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Benefits offered by this job

Remote-friendly
Optional in-person meetings at Apex,NC

Job summary

Security Journey is seeking a Senior Platform Engineer to own day-to-day platform operations across AWS and Kubernetes, with a focus on reliability, scale, and developer experience.

You will run EKS clusters, build self-service tooling, and improve CI/CD workflows using GitHub Actions and ArgoCD in a remote-first environment with an Apex, NC office optional for in-person collaboration.

Qualifications

  • 5+ years of experience in Platform Engineering, DevOps, SRE, or related roles.
  • Hands-on experience operating production workloads in AWS.
  • Strong Kubernetes experience (EKS preferred).
  • Experience with Terraform or equivalent IaC tooling.
  • Experience building or owning CI/CD systems.
  • Strong troubleshooting skills across networking, containers, distributed systems, and incidents.
  • Ability to balance immediate needs with long-term improvements.
  • Strong written communication in a remote-first environment.

Responsibilities

  • Own day-to-day platform operations across AWS infrastructure and Kubernetes environments.
  • Improve reliability, scalability, and performance of the learning platform.
  • Operate and evolve multiple EKS clusters across production and non-production.
  • Build internal self-service tooling and guardrails for developers.
  • Improve CI/CD workflows using GitHub Actions and GitOps with ArgoCD.
  • Drive observability improvements using DataDog, including dashboards and alerts.
  • Collaborate with software engineers, QA, product, and security teams to reduce friction.
  • Lead infrastructure changes end-to-end using Terraform and modern IaC practices.
  • Reduce toil through automation and thoughtful platform design.
  • Participate in on-call rotation and mentor teammates.

Skills

Go
Python
Ruby
React

Tools

AWS
Kubernetes (EKS)
Terraform
ArgoCD
GitHub Actions
DataDog

Job description

Senior Platform Engineer (AWS / Kubernetes)

Remote (United States)

Security Journey is hiring a Senior Platform Engineer to help scale and operate the platform behind our secure coding training products used by engineering organizations worldwide.

This is a hands-on role for an engineer who enjoys owning production systems, improving developer experience, and bringing order to fast-moving environments. You’ll help run the daily platform operation while driving long-term improvements in reliability, standardization, automation, and cost efficiency.

We are a remote-first company with an office in Apex, NC for optional in-person collaboration.

What You’ll Do
  • Own day-to-day platform operations across AWS infrastructure and Kubernetes environments.
  • Improve reliability, scalability, and performance of systems supporting our learning platform.
  • Operate and evolve multiple EKS clusters across production and non-production environments.
  • Build internal self-service tooling and engineering guardrails that help developers ship safely and independently.
  • Improve CI/CD workflows using GitHub Actions and GitOps practices with ArgoCD.
  • Drive observability improvements using DataDog, including dashboards, alerting, and incident response readiness.
  • Partner with software engineers, QA, product, and security teams to remove friction and increase delivery velocity.
  • Lead infrastructure changes end-to-end using Terraform and modern IaC practices.
  • Reduce operational toil through automation, standardization, and thoughtful platform design.
  • Participate in an on-call rotation focused on ownership, reliability, and continuous improvement.
  • Mentor teammates through collaboration, code review, and operational best practices.
Our Environment

We run a modern cloud-native stack with room to improve and meaningful ownership opportunities.

Infrastructure & Platform
  • AWS
  • Kubernetes / EKS
  • Terraform
  • ArgoCD
  • GitHub Actions
  • DataDog
Data & Messaging
  • PostgreSQL
  • Redis
  • Kafka
Languages & App Stack
  • Go
  • Python
  • Ruby
  • React
What We’re Looking For
Required
  • 5+ years of experience in Platform Engineering, DevOps, SRE, or related infrastructure roles.
  • Strong hands-on experience operating production workloads in AWS.
  • Strong Kubernetes experience (EKS preferred).
  • Experience managing infrastructure with Terraform or equivalent IaC tooling.
  • Experience building or owning CI/CD systems.
  • Strong troubleshooting skills across networking, containers, distributed systems, and production incidents.
  • Ability to balance immediate operational needs with long-term engineering improvements.
  • Strong written communication and comfort working in a remote-first environment.
  • U.S. citizenship and U.S.-based residency.
Nice to Have
  • Experience with GitOps workflows (ArgoCD preferred).
  • Experience with Datadog or modern observability platforms.
  • Experience supporting SOC 2 or regulated environments.
  • Experience with Kafka, PostgreSQL, or Redis in production.
  • Programming experience in Go or Python.
  • Experience building internal developer platforms or self-service tooling.
What Success Looks Like in Your First Year
  • Become a trusted owner of day-to-day platform operations.
  • Reduce interruptions through automation and better platform workflows.
  • Improve deployment consistency and developer self-service.
  • Strengthen reliability, alerting, and incident readiness.
  • Help modernize legacy areas while keeping delivery fast and pragmatic.
About Security Journey

Security Journey is the Enterprise AI Training & Capability Platform, helping organizations build the skills to use AI better and more securely. With deep roots in secure code training and secure development education, Security Journey now brings role-based, hands-on AI learning to the entire workforce - from developers building software with AI to teams across the business transforming how they work with it. Leaders gain visibility into where skills are growing, where risk is emerging and where successful AI practices are ready to scale.

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