Staff Cluster Infrastructure Engineer

The Staff Cluster Infrastructure Engineer will serve as a technical lead and hands-on driver for cluster infrastructure, automated provisioning, and orchestration platforms across our distributed storage ecosystem.

Responsibilities:

• Cluster Architecture and Deployment: Leading the deployment, management, and scaling of enterprise-grade Kubernetes clusters to orchestrate distributed storage infrastructure across cloud and bare-metal environments.
• Operator and Controller Development: Designing and implementing Kubernetes Custom Resource Definitions (CRDs) and custom operators/controllers to automate the lifecycle and management of complex storage systems.
• Control Plane and Automation: Developing robust control plane software, automation frameworks, and management tooling primarily using Go and Python.
• Scalability and Systems Engineering: Applying fundamental computer science principles to solve complex cluster orchestration, networking, and scalability challenges.
• Cross-Functional Collaboration: Collaborating with systems architects and storage engineers to ensure seamless integration between the underlying storage architecture and high-level deployment frameworks.
• AI Tooling Adoption: Actively integrating cutting-edge AI tools (e. g., GitHub Copilot, integrated IDE features) into engineering workflows to boost productivity and code quality across the team.
• Technical Leadership and Mentorship: Mentoring team members, setting operational standards, participating in architectural reviews, and guiding engineers on cluster infrastructure best practices.

Requirements:

• Bachelor's, master's, or Ph. D. degree in computer engineering, computer science, electrical engineering, or a related technical field.
• 7 to 10 years of hands-on professional experience in systems automation, platform engineering, or infrastructure engineering.
• Proven track record of designing, building, and maintaining production-grade Kubernetes environments at scale.

Technical Skills (Must-Haves):

• Solid foundation in computer science fundamentals (data structures, algorithms, operating systems, and computer network architecture).
• Deep expertise in Kubernetes: configuring, setting up, bootstrapping, securing, and managing production K8s clusters.
• Hands-on experience developing Kubernetes CRDs and custom resources/operators for complex storage or infrastructure workloads.
• Excellent programming skills in Go and Python for building system tools, control planes, and automation scripts.
• Strong Linux system administration and Linux scripting skills.
• Proficiency with modern dev toolchains and AI-assisted development tools (e. g., VS Code, GitHub Copilot).

Technical Skills (Good-to-Have):

• Knowledge of cloud and virtualization management platforms such as OpenStack or VMware vSphere/VMs.
• Familiarity with distributed storage systems (e. g., Ceph, S3, Lustre) from an operational and deployment perspective.

Soft Skills and Leadership:

• Strong technical leadership capability to drive implementation strategy and mentor engineering team members.
• Eagerness to integrate AI tools into the daily development workflow to maximize engineering throughput.
• Excellent problem-solving skills, system-level analytical thinking, and attention to detail.
• Ability to thrive and drive execution in a fast-paced, collaborative