Principal Platform Engineer
As a Principal Platform Engineer at Gradial, you will shape the foundation our platform runs on as we scale. You will work closely with the CTO and engineering team to make our systems faster, more resilient, and easier to operate in a high-growth environment. This is a hands-on individual contributor leadership role for someone who wants real ownership, high leverage, and the opportunity to define how platform reliability looks at an AI-native company.
What You’ll Own
Own the reliability, scalability, and operational health of Gradial’s production platform.
Lead the evolution of Kubernetes, CI/CD, observability, and infrastructure as code across the stack.
Set the standard for how we design, ship, and operate reliable systems.
Build the tooling and automation that help engineers move faster with more confidence.
Drive improvements in monitoring, alerting, incident response, and service readiness.
Partner with engineering to identify scaling risks early and solve them before they slow us down.
Influence the long-term direction of our platform across reliability, security, performance, and cost.
What We’re Looking For
5+ years of experience in platform engineering, infrastructure, SRE, DevOps, or related roles with direct ownership of production systems.
Proven success designing and operating production-grade infrastructure in fast-moving, high-growth environments.
Deep expertise in Kubernetes, cloud-native architecture, and container orchestration.
Strong experience with infrastructure as code, GitOps, CI/CD workflows, and modern deployment practices.
Strong command of observability and reliability fundamentals across metrics, logging, tracing, alerting, and incident response.
A track record of leading through influence, making sound technical decisions, and raising the bar across engineering teams.
Nice to Have
Familiarity with AI or ML infrastructure, including GPU provisioning, model deployment, or compute-intensive workloads.
Experience supporting cloud or multi-cloud environments with a focus on resilience and scale.
Comfort with TypeScript or Python for internal tooling and operational automation.