Software Golang Engineer (Kubernetes)

Gcore is a global provider of infrastructure and software solutions for AI, cloud, network, and security, with over 210 edge locations, 50+ cloud regions, and thousands of GPUs. The company collaborates with technology partners such as Intel, NVIDIA, Dell, and Equinix and supports a global team of 550+ professionals. The role focuses on building Kubernetes-native AI infrastructure and tooling for scalable inference and training workloads.

• Strong proficiency in Go programming with Kubernetes development experience including controllers and operators.
• Deep understanding of Kubernetes architecture, resource management, and container orchestration.
• Experience with Kubernetes APIs and custom resources (CRDs).
• Solid knowledge of cloud-native technologies and frameworks including Docker and Helm.
• Strong problem-solving skills for distributed systems.
• Excellent communication and teamwork abilities.

Nice to have:

• Experience with Python.
• Experience in AI/ML pipelines or integrating AI frameworks such as TensorFlow and PyTorch into Kubernetes.
• Understanding of GPU scheduling and optimization in Kubernetes.
• Knowledge of Kubernetes security best practices including role-based access control (RBAC) and container security.
• Contributions to open-source Kubernetes projects or cloud-native communities.

• Design and implement AI inference and model training cloud products optimized for Kubernetes, including autoscaling inference servers and distributed training jobs across GPU fleets.
• Write clean, efficient, and maintainable Go code for Kubernetes controllers, operators, and custom resources supporting AI workloads.
• Build APIs, CLIs, and developer tools to simplify deployment, lifecycle management, and monitoring of AI applications.
• Develop features optimizing serverless container workflows for AI, ensuring fast cold starts, resource-efficient scaling, and workload isolation.
• Contribute to system performance, reliability, and security with focus on AI-specific challenges such as GPU scheduling, job orchestration, and data throughput.
• Stay updated with Kubernetes ecosystem advancements (e.g., K8s-native ML tooling, scheduling improvements, SIGs) and influence product roadmap.

We provide equal opportunity to all applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity, gender expression, national origin, disability, or any other legally protected characteristics.