Senior Platform Reliability Engineer — Kubernetes, AI & Edge

WEBRIOT; Milwaukee (WI); Hybrid; USD 140,000 - 190,000; Full time

Job summary

WEBRIOT is seeking an experienced infrastructure-focused engineer to move between architecture, implementation, incidents, and customer teams. You will design platform capabilities, trace delivery failures, and ship durable systems that improve outcomes.

Your work will reduce production surprises and minimize dependence on external help, while teaching customers to own what remains. Expect collaboration across cloud, edge, and AI workloads with a focus on reliability and automation.

Qualifications

• Deep experience operating production infrastructure and debugging failure across multiple layers.
• Strong Infrastructure as Code, CI/CD, Linux, networking, containers, and Kubernetes fundamentals.
• The ability to write maintainable software or automation in at least one general-purpose language.
• Clear technical writing and direct communication under uncertainty.

Responsibilities

• Design and implement platform capabilities across cloud, Kubernetes, edge, and AI workloads.
• Trace delivery and reliability failures through code, infrastructure, telemetry, and team boundaries.
• Build automation, deployment paths, observability, recovery controls, and operational documentation.
• Lead technical conversations with engineers and executives without hiding tradeoffs behind jargon.
• Pair with customer teams so ownership transfers with the system instead of after it.

Skills

Infrastructure as Code

CI/CD

Linux

Networking

Containers

Kubernetes

Go

Python

TypeScript

Observability

Tools

Terraform

OpenTelemetry

Prometheus

Grafana

Argo CD

Flux

GitHub Actions

GitLab CI

AWS

Azure

GCP

Job description

WEBRIOT is seeking an experienced infrastructure-focused engineer to move between architecture, implementation, incidents, and customer teams. You will design platform capabilities, trace delivery failures, and ship durable systems that improve outcomes.

Your work will reduce production surprises and minimize dependence on external help, while teaching customers to own what remains. Expect collaboration across cloud, edge, and AI workloads with a focus on reliability and automation.