Job description

About Perry Weather Perry Weather is the weather safety standard for organizations that operate outdoors. We combine on-site weather hardware with a software platform that automates alerts, siren activations, and safety decisions for more than 3,000 organizations — from the PGA of America, the NFL, and MLB to Turner Construction, thousands of school districts, cities, and golf courses. We've grown 80%+ annually for five consecutive years, and are continuing to grow. We're headquartered in Dallas at The Centrum, in the Oak Lawn neighborhood, where our teams work together every day to help organizations make faster and safer decisions when weather puts people, assets, and operations at risk. About the Role We're looking for a Platform Engineer to help build and run the infrastructure the rest of engineering depends on. You'll partner closely with our Lead Platform Engineer, designing and delivering the work together, and own real surface area from the start: infrastructure as code, our Kubernetes environments, delivery pipelines, observability, and the guardrails that keep all of it safe to change. Engineering is your customer. Success in this role looks like fast service setup, uneventful deploys, and engineers who can diagnose a failing workload without asking for help. Engineering here also works with AI coding agents daily, which adds to the platform team's job: checks that catch generated infrastructure errors before they apply, scoped credentials and audit trails for automated actors, and cost reporting that accounts for agent usage. You'll use agents in your own work and help build these controls for everyone else. Responsibilities - Infrastructure as code. Write and maintain the Terraform that defines our cloud footprint, review changes for blast radius, and keep our modules usable by engineers outside the platform team. - Kubernetes and workloads. Run our clusters and the Helm-deployed services on them, including resource tuning, scaling behavior, and the failure modes that only show up under load. - Delivery pipelines. Build and maintain CI/CD in GitHub Actions so that builds, tests, and deploys are fast and dependable enough that engineers rely on them. - Observability and reliability. Improve the instrumentation, dashboards, and alerting that tell us how the platform is behaving, and make alerts specific enough that people act on them. - Cost and capacity. Track where our cloud spend goes, find the waste, and add controls that catch expensive changes before they ship. - Guardrails. Secrets management, least-privilege access, dependency and image scanning, and policy checks that catch mistakes during review. - AI and automated actors. Coding agents and automation are regular consumers of our platform. You'll give them scoped identities and audit trails, add the checks that catch generated infrastructure mistakes before they apply, and track what their usage costs alongside the rest of our spend. - On-call and incident support. Share the on-call rotation, respond when the platform degrades, and make the changes that prevent a repeat. Requirements - 4+ years in platform, infrastructure, DevOps, or backend engineering, with real ownership of production infrastructure - You're fluent in infrastructure as code. Terraform experience is ideal, but if you've come from another IaC tool, the fundamentals carry over. You've written and maintained IaC in production and know how to keep what's declared in code in sync with what's actually running - Working depth in a major cloud, including managed databases, networking, identity, and secrets. We're primarily on Azure, but AWS or GCP experience transfers Nice to Have - Kubernetes in production. You can take a failing workload, trace it through configuration, networking, and resource limits, and explain what went wrong to the engineer who owns the service - CI/CD you've built and debugged, ideally GitHub Actions. You've fixed a pipeline engineers had stopped trusting, and you can separate a failing test from failing infrastructure - Scripting in Python, Go, or Bash good enough to automate a manual process end to end and leave it maintainable for someone else - Observability work you've done yourself: instrumentation you added, a dashboard other people used, and an alert you tuned because it fired too often - On-call experience for production systems, including at least one incident you drove to resolution and wrote up afterward - Product instincts about internal tooling. You've built something for other engineers, watched them use it, and changed it based on what you saw - Fluency with AI-native engineering tools and agentic workflows (e.g., terminal-native coding agents, LLM-assisted code refactoring and generation) to multiply technical output and speed up development cycles - Least-privilege credential design for automated systems: CI service accounts, scoped tokens, short-lived credentials, and audit trails. Agents are the newest consumers of that work, and the principles carry over Note: We're looking for someone with broad exposure who not only is comfortable going deep when needed but actually wants to. You don't need to be an expert in every requirement above. If you're strong in a few areas and excited to learn the rest, we'd love to hear from you. Don't let the nice-to-haves stop you from applying! Benefits - You'll want to come into the office. Our Oak Lawn office isn't just a place to sit — it's where ideas move fast and culture stays strong. The whole team is here Monday through Friday, which means real collaboration, no chasing people down over Slack, and a genuinely fun place to spend your work days. - Your wellbeing is covered. Competitive health insurance, 401(k) with employer matching, and a full suite of voluntary benefits, because you shouldn't have to think twice about the basics. - Good people, good times. Monthly All-Hands, Office Olympics, happy hours, and more. We take the work seriously and the culture seriously too. - You're getting in early, and that matters. We're growing fast, but the biggest opportunities are still ahead. The people joining now will help shape what Perry Weather becomes.

Requirements

Must-haves

Engineering is your customer. Success in this role looks like fast service setup, uneventful deploys, and engineers who can diagnose a failing workload without asking for help.
Infrastructure as code. Write and maintain the Terraform that defines our cloud footprint, review changes for blast radius, and keep our modules usable by engineers outside the platform team.
Kubernetes and workloads. Run our clusters and the Helm-deployed services on them, including resource tuning, scaling behavior, and the failure modes that only show up under load.
Delivery pipelines. Build and maintain CI/CD in GitHub Actions so that builds, tests, and deploys are fast and dependable enough that engineers rely on them.
Observability and reliability. Improve the instrumentation, dashboards, and alerting that tell us how the platform is behaving, and make alerts specific enough that people act on them.
Cost and capacity. Track where our cloud spend goes, find the waste, and add controls that catch expensive changes before they ship.
Guardrails. Secrets management, least-privilege access, dependency and image scanning, and policy checks that catch mistakes during review.
On-call and incident support. Share the on-call rotation, respond when the platform degrades, and make the changes that prevent a repeat.
4+ years in platform, infrastructure, DevOps, or backend engineering, with real ownership of production infrastructure
Working depth in a major cloud, including managed databases, networking, identity, and secrets. We're primarily on Azure, but AWS or GCP experience transfers

Nice-to-haves

Kubernetes in production. You can take a failing workload, trace it through configuration, networking, and resource limits, and explain what went wrong to the engineer who owns the service
CI/CD you've built and debugged, ideally GitHub Actions. You've fixed a pipeline engineers had stopped trusting, and you can separate a failing test from failing infrastructure
Scripting in Python, Go, or Bash good enough to automate a manual process end to end and leave it maintainable for someone else
Observability work you've done yourself: instrumentation you added, a dashboard other people used, and an alert you tuned because it fired too often
On-call experience for production systems, including at least one incident you drove to resolution and wrote up afterward
Product instincts about internal tooling. You've built something for other engineers, watched them use it, and changed it based on what you saw
Fluency with AI-native engineering tools and agentic workflows (e.g., terminal-native coding agents, LLM-assisted code refactoring and generation) to multiply technical output and speed up development cycles
Least-privilege credential design for automated systems: CI service accounts, scoped tokens, short-lived credentials, and audit trails. Agents are the newest consumers of that work, and the principles carry over

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

restkubernetesaici/cdazureawsgcppythongollm

Platform: ashby
Effort: quick

Benefits

Benefits detected in the listing.

Health Insurance

401(K)