Site Reliability Engineer 2

If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others.

If you don’t think you meet all of the criteria below but are still interested in the job, please apply. Nobody checks every box - we’re looking for candidates that are particularly strong in a few areas, and have some interest and capabilities in others.

As a Site Reliability Engineer, you’ll join the global Platform SRE team responsible for building, operating, and scaling Kong’s multi-region SaaS platform that powers the world’s API connectivity.

You’ll design, automate, and run production systems serving thousands of customers across AWS, GCP, and Azure. You’ll work on everything from multi-region Kubernetes clusters to service mesh and gateway architectures, ensuring the reliability, scalability, and security of Kong’s SaaS offerings.

This is a hands-on role ideal for engineers who thrive on running production SaaS systems at scale, automating operations, and continuously improving performance, resilience, and deployment pipelines.

Operate and scale Kong’s global SaaS platform (Konnect), ensuring reliability, availability, and performance across regions and clouds.

Build, automate, and maintain Kubernetes-based infrastructure and deployment workflows using Terraform/Terragrunt, Helm, and ArgoCD.

Design, maintain, and optimize multi-region data and caching layers — including PostgreSQL, Redis, ClickHouse, and Druid — for high availability and low latency.

Operate and improve Kong Gateway and Kong Mesh environments supporting hybrid and distributed architectures.

Develop and maintain CI/CD pipelines and GitOps workflows to automate service delivery and ensure consistent infrastructure changes.

Enhance observability and incident response readiness through systems like Datadog, Prometheus, Grafana, and Thanos, defining and tracking SLOs.

Collaborate closely with development and security teams to ensure smooth operation of SaaS services in compliance with reliability, security, and regulatory standards.

Participate in a global 24/7 on-call rotation and drive continuous improvement of operational playbooks and postmortem practices.

Lead and contribute to scaling initiatives that improve elasticity, reliability, and cost-efficiency across the SaaS platform.

BS in Computer Science or equivalent practical experience.

Proven experience managing SaaS or PaaS systems at enterprise scale (multi-region, multi-tenant, secure environments).

Deep expertise in Kubernetes, including debugging cluster/networking issues and designing for fault tolerance and scalability.

Strong proficiency with Infrastructure as Code tools like Terraform or Terragrunt.

Experience with CI/CD pipelines and GitOps workflows (ArgoCD, Atlantis, Helm).

Proficiency in one or more programming languages (Go, Python, Bash) for automation and tooling.

Solid understanding of Linux/Unix systems, networking (DNS, TLS/SSL, HTTP), load balancers and distributed systems.

Familiarity with streaming systems like Kafka and observability platforms (Datadog, Prometheus, Grafana).

Experience working in a 24/7/365 production support environment.

Hands-on experience with Kong Gateway, Kong Mesh, or similar service connectivity technologies.

Experience operating ClickHouse, Druid, or other time-series and analytics databases.

Experience managing PostgreSQL and Redis in multi-region configurations.

Working knowledge of AWS networking (PrivateLink, Transit Gateway, VPC Peering, Firewalls), Azure VNet, or GCP NCC.

Strong understanding of disaster recovery, resiliency testing, and compliance-driven reliability practices.

Kong Inc., a leading developer of API and AI connectivity technologies, is building the infrastructure that powers the agentic era. Trusted by the Fortune 500 and startups alike, Kong's unified API and AI platform, Kong Konnect, enables organizations to secure, manage, accelerate, govern, and monetize the flow of intelligence across APIs and AI models. For more information, visit .