Senior Engineering Manager - Kubernetes Development Platform (San Jose)

Hungry Humble HonestThe OpportunityWe 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.About the TeamWe 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.Your RoleAs 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-tenancyDrive the design of large-scale distributed systems, evolving toward global control planes and cell-based architecturesLead a team of engineers to build AI-native infrastructure, including GPU-aware scheduling, resource isolation, and workload orchestrationPartner closely with Product and cross-functional teams to translate enterprise and AI use cases into platform capabilitiesEstablish a strong operational excellence culture, including SLOs, reliability engineering, and production readinessSimplify complex infrastructure into intuitive, consumable platform experiences for enterprise usersYou will play a key role in shaping a platform that brings hyperscaler-like capabilities into enterprise data centers.What You Will BringStrong Engineering LeadershipProven experience leading and scaling high-performing engineering teamsAbility to drive clarity, ownership, and execution in complex, ambiguous problem spacesDeep Technical ExpertiseStrong understanding of distributed systems at scaleHands-on familiarity with cloud platforms, infrastructure systems, or PaaS offeringsExperience 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 domainPlatform & Systems ThinkingExperience designing multi-tenant platforms with clear abstractions (projects, quotas, policies)Familiarity with multi-cluster / fleet management and large-scale system designAbility to balance long-term architecture with near-term deliveryAI / Infrastructure Awareness (Preferred but Not Required)Exposure to AI/ML workloads or GPU-based systems is a plusEqually, we welcome strong platform engineers who are excited to grow into AI infrastructure—this role offers the opportunity to learn and build in the rapidly evolving space of GPU scheduling, training, and inference systemsExecution & Operational ExcellenceTrack record of delivering reliable, production-grade systemsExperience with SLOs, observability, incident management, and lifecycle operationsCollaboration & InfluenceStrong ability to work across product, hardware, and field teamsEffective executive-level communication and stakeholder managementThe visa sponsorship is not available for this role at this time.Work ArrangementHybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. In locations where our workplace policy applies (i.e. San Jose, Durham, Mexico City, Bangalore, Pune, Hoofddorp, Belgrade, Barcelona, Singapore, Sydney and Tokyo), employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in-office resources. Workplace type may vary based on location and team requirements. Please speak with your recruiter for details. Additional team-specific guidance and norms will be provided by your manager.The pay range for this position at commencement of employment is expected to be between USD $195,200 and USD $391,200 per year.However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment.If hired, employees will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. Our application deadline is 40 days from the date of posting. In good faith, the posting may be removed prior to this date if the position is filled or extended in good faith.--