Site Reliability Engineer, K8s
Description
WebMD and its affiliates is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, ancestry, color, religion, sex, gender, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.
Build the platform behind PulsePoint
PulsePoint operates large-scale data and advertising platforms that power business-critical services used every day across the company.
Our Platform Engineering team owns the foundation that enables engineering teams to move quickly and safely. We build and operate the infrastructure that supports Kubernetes workloads, data platforms, developer tooling, observability and production operations at scale.
Unlike many cloud-only environments, we own the full lifecycle of the infrastructure - from bare-metal hardware and networking to Kubernetes, observability and developer experience.
The environment supports large-scale Kubernetes workloads, multi-petabyte data systems and business-critical services used across multiple engineering organizations.
We're looking for an experienced engineer to help shape its next stage of growth.
This is a hands-on role focused on architecture, reliability, automation and operational excellence. You will work on complex distributed systems, drive platform improvements and help shape the technical direction of infrastructure across the company.
What you'll work on
You'll help design, build and operate the Kubernetes platform used across PulsePoint.
Examples of challenges you may work on include:
Platform architecture and Kubernetes lifecycle management
Reliability, observability and incident response
Infrastructure automation and GitOps workflows
Networking, service connectivity and platform security
Developer experience and self-service platform capabilities
Large-scale distributed systems running on bare-metal infrastructure
Technology
You'll work in an environment that includes:
Kubernetes and platform services
Multi-petabyte data infrastructure
Bare-metal and cloud environments
GitOps and infrastructure automation
Modern observability and reliability engineering practices
Technologies commonly used across the environment include Kubernetes, ArgoCD, Puppet, Terraform, OpenTelemetry, Prometheus, Alertmanager, Kafka, Redis and Ceph.
Experience with every technology is not required.
Who we’re looking for
Success in this role is not measured by the number of tickets closed or clusters operated. Success means building platform capabilities that make engineering teams more reliable, productive and autonomous.
We're especially interested in engineers who:
Have operated production infrastructure at meaningful scale
Understand how distributed systems fail and recover
Prefer automation over repetitive operational work
Enjoy simplifying systems rather than adding complexity
Take ownership beyond the boundaries of a single component
Why this role
This is not a ticket-driven operational role.
You'll help define platform architecture, influence engineering standards and work on infrastructure that supports multiple engineering organizations.
The engineer joining this role is expected to become a key technical contributor shaping the future of the platform.
Hiring process
At the moment, we are not considering automation of technical screening, so as not to reduce the incoming flow of candidates. In the future we can look to the short technical screening via TestDome (or something else), when we will send unique URL to test environment for testing kubeadm, kubectl, control plane and etc. And candidate can use any documentation or AI assistants during the assessment, because goal is test ability to solve practical tasks within the limited time.
In hiring process it will looks like:
- Technical screening (~30m)
Solve a practical problem with all available tools in a limited time
Introductory conversation (~30m)
Learn about your background and discuss the role.Technical discussion (~60m)
Deep dive into systems engineering, Kubernetes and operational experience.Architecture discussion (~60m)
Explore platform design, distributed systems and technical decision making.Leadership conversation (~30m)
Meet engineering leadership and discuss team, strategy and long-term direction.