Senior Kubernetes Control Plane Architect

Bitdeer Technologies Group

Singapore

On-site

SGD 120,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Open workspaces

Training and mentoring

Fast-growing environment

Networking with pioneers

Development opportunities

Job summary

Bitdeer is seeking an experienced software engineer to design and operate scalable control plane architectures for AI and cloud workloads. You will collaborate with cross-functional teams to deliver robust Kubernetes-based solutions and drive reliability across regions.

The role requires 8+ years of engineering experience, deep Go expertise, and a track record with Kubernetes, multi-tenancy, and large distributed systems. The position offers a dynamic, fast-moving environment in Singapore.

Qualifications

8+ years of software engineering experience with Go.
Extensive experience contributing to or extending the Kubernetes ecosystem (Operators, API Server, etcd).
Proven track record operating, debugging, and scaling large-scale distributed systems in production.
Deep understanding of multi-tenancy models, cluster federation, and API governance in cloud-native environments.
Familiarity with infrastructure automation (Terraform, CI/CD pipelines) and managed cloud services.
Strong technical leadership skills; ability to influence architectural decisions and align cross-functional teams.
Excellent communication skills, with the ability to translate complex system requirements into milestones.
Experience working in high-velocity, high-growth engineering environments is highly preferred.

Responsibilities

Design and implement scalable control plane architectures using tools like Cluster API to enable fleet-wide automation.
Develop custom Kubernetes Operators and CRDs to streamline lifecycle management and orchestration.
Optimize etcd performance and ensure rock-solid state management across distributed cloud regions.
Implement secure, multi-tenant isolation mechanisms at the API server layer to support enterprise-grade security and tenancy.
Architect solutions for zero-downtime upgrades and multi-cluster federation to provide a seamless user experience for our AI customers.
Collaborate with AI Scheduling and Fabric engineering teams to ensure the control plane integrates tightly with GPU orchestration layers.
Lead design reviews and mentor engineers to uphold high standards of distributed systems architecture across the team.
Drive platform reliability by identifying and mitigating failure modes in the control plane chassis before they impact customer training or inference jobs.