Platform Software Engineer II Kubernetes Golang & Developer Platform

The ideal candidate is a hands-on platform software engineer with strong experience in Golang, Kubernetes Custom Resource Definitions (CRDs), custom operators, GraphQL backend development, and internal developer platforms. This individual should enjoy building cloud-native engineering solutions, developing CLI tools, improving developer workflows, and troubleshooting complex systems. The successful candidate will contribute across the software lifecycle, including application development, build systems, testing, CI/CD, release automation, infrastructure tooling, and platform operations.

Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

• At least 3 years of professional software engineering experience.
• Strong proficiency in Golang or demonstrable professional experience developing software in Golang.
• Hands-on experience with Kubernetes Custom Resource Definitions (CRDs) and custom operators/controllers.
• Experience developing Golang-based CLI tools.
• Experience developing GraphQL backends using Golang, including schemas, types, queries, and mutations.
• Experience contributing to or engineering internal developer platforms or developer productivity tooling.
• Experience developing software in Linux or macOS environments.
• Understanding of software engineering fundamentals, including data structures, algorithms, testing, and system design.
• Familiarity with distributed systems and modern software architectures.
• Experience with Git-based source control workflows, such as GitHub or GitLab.
• Experience with containerized applications and Kubernetes.
• Strong analytical, troubleshooting, and problem-solving skills.
• Effective written and verbal communication skills and the ability to collaborate across engineering teams. *

Preferred Qualifications Experience with Google Cloud Platform (GCP) and cloud-native technologies.

• Experience with platform engineering practices, including GitOps, CI/CD, OCI artifacts, test infrastructure, and build systems.
• Experience with infrastructure-as-code and developer productivity tooling.
• Experience designing and supporting distributed systems with attention to scalability, performance, availability, and observability.
• Experience with large-scale build systems such as Bazel.
• Familiarity with Agile, Scrum, and iterative software development practices.

• Experience contributing to open-source projects. *

• Exposure to AI application development using large language model (LLM) platforms, agentic workflows, tool integrations, prompt engineering, and model evaluation.