This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Golang/Kubernetes Engineer based in United States.
This is a senior engineering opportunity focused on building and evolving a critical Kubernetes operator for a distributed database platform.
You’ll own architecture and development across lifecycle management, scaling, backup, replication, and high availability.
The role sits at the intersection of Go, Kubernetes, cloud infrastructure, and distributed systems.
You’ll help define best practices for operating stateful workloads reliably in production environments.
Your work will directly support enterprise-grade AI and data applications, including deployments in regulated and government cloud environments.
You’ll collaborate closely with experienced engineering teams while solving complex infrastructure and reliability challenges.
This is a hands-on role with significant technical ownership, influence, and opportunities to shape core platform capabilities.
Accountabilities
Lead the architecture, design, and development of the Kubernetes operator, establishing scalable and maintainable technical foundations.
Own core operator functionality covering application lifecycle management, scaling, backup, replication, upgrades, and cluster operations.
Design and implement capabilities that support high availability, performance, consistency, and stability for stateful database workloads running on Kubernetes.
Define and promote engineering best practices for deploying, operating, and automating stateful systems within Kubernetes environments.
Collaborate with engineering and product teams to align operator capabilities with enterprise requirements, cloud environments, and customer needs.
Support the extension of the platform into AWS GovCloud and contribute to projects supporting government environments.
Troubleshoot complex issues involving Kubernetes, distributed systems, storage, replication, and cloud infrastructure.
Contribute to observability, metrics, automation, cluster lifecycle management, and operational reliability.
Drive technical discussions, review code, mentor other engineers, and create clear architecture and design documentation.
Help ensure solutions meet production-grade standards for reliability, scalability, maintainability, and security.
4+ years of professional programming and cloud experience, with substantial hands-on software engineering responsibility.
Strong expertise with Kubernetes, including Custom Resource Definitions (CRDs), operators, deployments, custom resources, and Kubernetes-native lifecycle management.
Strong proficiency in Go, including a solid understanding of concurrency, storage, and distributed-system concepts.
Demonstrated experience designing and managing production-grade distributed databases or other stateful systems.
Practical knowledge of storage management and data replication, including persistent volumes, snapshots, backups, failover, and cluster scaling.
Hands-on experience with Kubernetes storage concepts such as PersistentVolumes, PersistentVolumeClaims, local storage, volume resizing, and storage-performance optimization.
Strong cloud engineering experience, particularly with AWS; familiarity with AWS GovCloud is highly valued.
Operational mindset with experience managing upgrades, migrations, observability, automation, and production cluster lifecycles.
Ability to diagnose and resolve complex infrastructure and distributed-systems problems.
Strong technical communication skills, including the ability to lead discussions, review code, write design documents, and produce clear technical documentation.
Demonstrated ability to mentor engineers and influence technical direction across teams.
U.S. citizenship is required due to the nature of the supported government project.
An active U.S. security clearance is preferred.
Fully remote position for candidates based in the United States.
Opportunity to work on cutting-edge AI, data, cloud, and distributed infrastructure.
Significant technical ownership over a critical Kubernetes-based platform component.
Opportunity to influence how enterprise customers deploy stateful systems and AI-driven applications in production.
Collaboration with experienced engineering, product, and business professionals.
Exposure to enterprise and government cloud environments, including AWS GovCloud.
Opportunity to contribute to the evolution of contextual data infrastructure for modern AI applications.
A technically challenging environment focused on innovation, reliability, scalability, and real-world impact.

