Software Engineer Ii, Infrastructure Security

Klaviyo Klaviyo · Enterprise · Dublin, Ireland · Engineering

Software Engineer II, Infrastructure Security at Klaviyo. This role focuses on building and operating cloud-native security services and platforms to ensure engineers can develop secure software at high speed. Responsibilities include designing, building, and maintaining security services, improving system availability and scalability, and collaborating on system design. The role requires experience with Python/Go, AWS, Kubernetes, and distributed systems, with a focus on security, reliability, and performance.

What you'd actually do

  1. Design, build, and maintain cloud-native security services used across Klaviyo
  2. Own meaningful components and services end to end, from implementation through production operation
  3. Improve the availability, scalability, latency, and efficiency of infrastructure security systems
  4. Collaborate with senior engineers on system design and architecture, contributing ideas and technical solutions
  5. Identify performance, reliability, and security issues in distributed systems and drive improvements

Skills

Required

  • building and operating cloud-native, distributed systems in production
  • writing production-quality code in Python or Go
  • hands-on experience with AWS (or a similar cloud provider)
  • experience with containers and orchestration platforms such as Kubernetes
  • owning services and features independently
  • fundamentals of scalable, multi-tenant architectures and secure system design
  • reliability, performance, observability, and security
  • participating in on-call and responding to production issues
  • clear communication, collaboration, and problem-solving
  • modern developer tooling, including AI-powered tools

Nice to have

  • building or integrating security-focused systems (e.g. secrets management, IAM, authn/z, policy enforcement)
  • Familiarity with service meshes, API gateways, or zero-trust architectures
  • Experience improving performance in distributed systems or debugging complex multi-service workflows

What the JD emphasized

  • cloud-native, distributed systems
  • Python or Go
  • AWS (or a similar cloud provider)
  • containers and orchestration platforms
  • Kubernetes