Top Tech Jobs & Startup Jobs in Denver & Boulder, CO

Design and develop the backend of the vCluster Platform using Go and deep Kubernetes expertise. Own features end to end, from technical design through release, while solving complex systems and multi-tenancy challenges. Contribute to open-source projects and Kubernetes community initiatives, build scalable isolation and resource-sharing solutions, and operate autonomously in a fast-growing startup environment.

Own post-sales customer outcomes for a technical SaaS platform. Lead onboarding, architecture workshops, integrations, success planning, adoption, business reviews, renewals, and expansion. Build relationships with executives, platform engineers, and DevOps teams while providing credible guidance on Kubernetes, RBAC, tenant isolation, and cloud infrastructure. Identify risks and growth opportunities, articulate business value, and advocate for customer needs internally.

Lead customer deployments of Kubernetes and vCluster on bare-metal GPU infrastructure, configuring GPU nodes, networking, storage, RDMA, and InfiniBand. Validate production-ready managed Kubernetes environments, troubleshoot complex infrastructure, transfer operational knowledge, document reusable deployment playbooks, and provide feedback to Engineering and Product. Support pre-sales proof-of-value engagements and help AI cloud and factory customers independently operate and scale their platforms.

Lead product direction for cloud-native GPU infrastructure and Kubernetes virtualization. Translate business priorities into technical specs, run alpha/beta validations, engage platform-engineer customers, define market positioning, and align engineering, sales, and marketing to ship and support scalable multi-tenant GPU platforms.

Lead architecture and execution of vNode runtime integration with containerd and the kubelet, define and test namespace-based isolation primitives, mentor engineers, run design reviews, operate internal tenant clusters, and represent the project in upstream communities and conferences.

Lead end-to-end GPU-focused Kubernetes deployments from bare metal to production-ready vCluster environments. Configure and troubleshoot GPU nodes (GPU Operator, CUDA, RDMA/InfiniBand), CNI and storage (CSI, Ceph/Rook/Weka/Longhorn), validate managed K8s, produce playbooks, transfer knowledge to customers, and feed infrastructure learnings back to Product and Engineering while supporting pre-sales proofs of value.

Lead end-to-end post-sales customer success for vCluster: onboard customers, build success plans, drive adoption, articulate business value, run executive reviews, design deployment architectures, and own renewals and expansion while advocating customer needs to Product and Engineering.

Design and validate partner reference architectures, enable partner and field teams, run partner-sourced POCs and demos, stand up partner Centers of Excellence, and cultivate technical and executive relationships with strategic GPU and cloud partners to scale channel-driven pipeline.