Principal Platform Engineer

Engineering and Infrastructure

You have a track record of owning the architectural direction of complex, high-stakes Platform workstreams — you've made the hard calls, been accountable for the outcomes, and learned from the experiences that didn't go as planned

You've designed and owned CI/CD systems at enterprise scale — defined the strategy, rationalized toolchains, and built governance models that let large organizations move fast without losing control

You've built and led cloud-native platform adoption in complex production environments — whether that's Kubernetes, managed container services, or other orchestration platforms — and built or overseen the platform engineering layer that makes it operable for teams who aren't infrastructure specialists

You've built and owned IaC systems that organizations genuinely depend on — module design, remote state management, drift detection, and migrating existing infrastructure into code without breaking production systems

You've built platform engineering work that demonstrably changed how engineering teams operate — internal developer platforms, self-service tooling, automated governance — reducing toil and improving delivery quality

You've implemented DevSecOps practices in real enterprise environments — secure pipelines, secrets management, policy as code, automated compliance — making security a first-class engineering concern

You've built observability programs that changed how teams behave — systems and culture that make engineers capable of understanding and operating what they build

AI and Intelligent Systems

You've integrated AI capabilities into real Platform and platform workflows — intelligent pipeline automation, AI-augmented developer tooling, or operational automation — and you can speak to the architecture, the tradeoffs, and what actually worked

You have enough depth in LLM capabilities and agentic patterns to make architectural decisions about where and how to apply them in a Platform context, and guide your team through implementation that holds up in production

You can have a credible conversation with client technical leaders about where AI creates genuine leverage — grounded in what's real

You use AI coding tools like Claude, Cursor, or Windsurf as a daily driver — and you actively champion adoption on your team because you've seen the compounding impact on quality and speed