Engineering Manager

Hungry Humble Honest   The Opportunity We are looking for a Senior Engineering Manager to lead the design, development, and scaling of a next-generation Kubernetes platform powering enterprise environments. This platform will serve as the foundation for   AI/ML workloads ,   GPU infrastructure , and enterprise applications, delivering hyperscaler-like capabilities in on-prem and hybrid deployments.   You will lead a team responsible for building a production-grade, globally scalable Kubernetes platform, including   cluster lifecycle ,   fleet management ,   multi-tenancy , and deep integration with compute (CPU/GPU), networking, and storage systems.

We are building a next-generation   Kubernetes   platform for   enterprise AI and infrastructure , designed to bring hyperscaler-grade capabilities into on-prem environments. The team owns the full stack—from   cluster lifecycle   and   fleet management   to multi-tenancy and   AI workload   orchestration (including GPUs).   Our charter is to enable enterprises to run   mission-critical   and   AI workloads   at massive scale, with a strong focus on simplicity, reliability, and performance. We operate as a highly collaborative, globally distributed team spanning the US and India, working closely with product, hardware, and field organizations. You will report to the Director of Engineering, who embodies a leadership style that emphasizes strong managerial expertise, technical involvement, and collaboration with engineers. The work setup for this role operates in a hybrid environment, with a strong preference for local candidates. While specific days for in-office attendance are not strictly defined, there is an expectation for the new hire to participate in office activities for certain interviews and collaborative sessions, fostering effective team interaction.

As a Senior Engineering Manager, you will lead the development of a scalable, enterprise-grade Kubernetes platform that powers AI and mission-critical workloads in on-prem and hybrid environments.   You will: Own end-to-end delivery of key platform capabilities, including cluster lifecycle, fleet management, and multi-tenancy Drive the design of large-scale distributed systems, evolving toward global control planes and cell-based architectures Lead a team of engineers to build AI-native infrastructure, including GPU-aware scheduling, resource isolation, and workload orchestration Partner closely with Product and cross-functional teams to translate enterprise and AI use cases into platform capabilities Establish a strong operational excellence culture, including SLOs, reliability engineering, and production readiness Simplify complex infrastructure into intuitive, consumable platform experiences for enterprise users   You will play a key role in shaping a platform that brings hyperscaler-like capabilities into   enterprise data centers .

Strong Engineering Leadership Proven experience leading and scaling high-performing engineering teams Ability to drive clarity, ownership, and execution in complex, ambiguous problem spaces   Deep Technical Expertise Strong understanding of   distributed systems at scale Hands-on familiarity with cloud platforms, infrastructure systems, or PaaS offerings Experience building   large, meaningful production systems   (cloud platforms, infrastructure, or PaaS) Kubernetes experience is desirable , but not required—we welcome leaders who are excited to   learn Kubernetes deeply   and apply strong systems fundamentals to this domain   Platform & Systems Thinking Experience designing multi-tenant platforms with clear abstractions (projects, quotas, policies) Familiarity with multi-cluster / fleet management and