
Senior Site Reliability Engineer - Volcano
What you need
- BS in CS or equivalent; Staff/Principal IC level
- SRE practices for developer platforms at greenfield stage
- Kubernetes multi-tenant cluster design and networking expertise
What you'll do
- Own Volcano reliability: SLOs, error budgets, incident response
- Build multi-region Kubernetes infrastructure and data plane
- Establish GitOps CI/CD with ArgoCD, Helm, Terraform
- Harden multi-tenant PostgreSQL, Redis, and object storage
- Instrument services with SLIs using Datadog, Prometheus, Grafana
Are you ready to unlock intelligence?
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.
About The Role:
Kong is building Project Volcano, an internal developer platform purpose-built for Kong's engineering ecosystem. Volcano will provide teams with on-demand preview environments, edge deployments, managed PostgreSQL, auth, realtime, and storage APIs all deeply integrated with Kong products.
As the Senior SRE for Volcano, you will be the reliability voice for this platform. This role is a strategic initiative driven by the Office of the CTO (OCTO). You will partner directly with engineering leadership to define the platform's reliability posture. This is a high-visibility, high-impact role with direct influence on Kong's next generation developer platform.
What You'll Do:
Own reliability for Volcano end-to-end: Define and drive SLOs, error budgets, and incident response practices for all Volcano services — edge deployments, managed Postgres, auth, realtime, storage, and the control plane.
Contribute to the platform's infrastructure: Design and build the multi-region Kubernetes infrastructure, networking, and data plane that powers Volcano's edge deployment pipeline and backend-as-a-service capabilities.
Build the GitOps and CI/CD backbone: Establish deployment automation, canary pipelines, and preview environment provisioning using ArgoCD, Helm, and Terraform/Terragrunt — setting patterns the broader team will follow.
Scale managed data services: Design, operate, and harden multi-tenant PostgreSQL clusters, Redis caching layers, and object storage — with a focus on data isolation, performance, and disaster recovery.
Drive observability from day one: Instrument every Volcano service with meaningful SLIs; build dashboards, alerts, and runbooks using Datadog, Prometheus, and Grafana before services go live, not after incidents.
Lead cross-functional reliability work: Collaborate with the OCTO team, product engineering, and security to bake reliability and compliance into Volcano's architecture — not bolt it on later.
Evaluate and adopt emerging technologies: Given Volcano's greenfield nature, evaluate and make architectural decisions on edge runtimes, serverless compute, vector databases, and AI-native infrastructure components.
What You'll Bring:
BS in Computer Science or equivalent; substantial experience at Staff or Principal IC level in SRE/Platform Engineering.
Proven track record building SRE or platform engineering practices for developer-facing platforms or PaaS/SaaS products — ideally at greenfield stage.
Kubernetes expertise: multi-tenant cluster design, networking (CNI, service mesh, ingress), autoscaling, and security hardening.
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About Kong:
Kong Inc., the AI Connectivity Company, is building the connectivity layer of AI. Trusted by the Fortune 500® and AI-native startups alike, Kong’s unified API and AI platform enables organizations to secure, manage, accelerate, govern, and monetize the flow of intelligence across APIs and AI traffic — on any model, any cloud. For more information, visit www.konghq.com.
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About Kong
Powering the API World. No AI without APIs. Kong enables any company to become an API-first company. Kong’s unified cloud native API platform is easy to use and works in any environment — unleashing developer productivity, automating security, and boosting performance of APIs and microservices at scale.
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