Platform Engineering

Platform Engineer NeuBird AI is scaling rapidly and we need a platform engineer who can build the internal tools and infrastructure that make our engineering teams more productive. You'll create self-service platforms, streamline developer workflows, and eliminate friction that slows down shipping.

Build and maintain internal platforms that power engineering productivity at NeuBird. You'll design developer tools and self-service systems that let engineers deploy code, provision infrastructure, and debug issues without waiting for platform team intervention. This means building CLI tools, internal APIs, automation frameworks, and abstractions that hide complexity while maintaining flexibility.

You'll work on our Kubernetes platform, creating deployment patterns and guardrails that make it easy to do the right thing and hard to break production. You'll implement infrastructure as code patterns, build CI/CD improvements that speed up feedback loops, and create observability tooling that helps engineers understand their services in production. You'll also maintain our developer documentation, run internal workshops on platform capabilities, and gather feedback to prioritize platform improvements.

This means understanding what slows engineers down—whether that's slow builds, complex deployment processes, or missing monitoring—and building solutions that scale across the engineering organization. You'll partner with SRE on reliability requirements, work with security on compliance needs, and ensure platform changes don't break existing workflows.
You have 3-5 years building internal platforms or infrastructure tooling, ideally at a company with multiple engineering teams sharing common infrastructure. You're deeply experienced with Kubernetes (building platforms on top of it, not just using it), infrastructure as code (Terraform, Helm, Kustomize), and CI/CD systems. You understand AWS and Azure services, have built APIs and CLI tools, and know how to design abstractions that are both simple to use and flexible enough for diverse use cases.

You've worked with Docker, understand container orchestration, and know how to debug when deployments fail. You're comfortable with at least one programming language for building tooling (Python, Go, or similar) and can write clear documentation that actually helps people. You measure success by how much faster engineers can ship, not by how impressive your infrastructure is. You can gather requirements from engineering teams, prioritize platform work based on impact, and know when to build versus adopt existing tools.

We're building the next generation of AI-powered DevOps intelligence. Join a well-funded team that's moving fast, shipping constantly, and building something genuinely differentiated in a massive market.