Top Tech Jobs & Startup Jobs

Design, build, and operate high-throughput AI lab, datacenter, colocation, corporate, campus, and cloud networks. Responsibilities include switching and routing, network segmentation and security, hardware and cabling support, hybrid connectivity, monitoring, capacity planning, automation, documentation, incident response, and on-call participation. The role requires regular hands-on work at Silicon Valley datacenter facilities and coordination with remote-hands providers elsewhere.

Lead an engineering organization building secure enterprise container and Kubernetes platforms. Define technical strategy, improve platform resilience and operational excellence, embed security throughout the SDLC, balance feature delivery with stability, hire and develop engineering talent, and collaborate with product leaders, executives, and enterprise customers.

Design and build Kubernetes-based LLM serving infrastructure, including GPU scheduling, scaling, model lifecycle management, Helm packaging, enterprise and offline deployments, API integrations, and production observability. Develop across a multi-service Go codebase, contribute design documentation and reviews, and help guide engineering direction. The role requires strong Kubernetes, distributed systems, CI/CD, and infrastructure-as-code expertise, with GPU, inference, or adjacent systems experience.

Design and build Go-based storage control-plane services, CSI drivers, integrations, and tooling for Kubernetes AI and compute workloads. Automate storage provisioning using Terraform/OpenTofu and GitOps tools, support hybrid and bare-metal deployments, and develop observability for performance and reliability. Integrate enterprise storage platforms such as Dell PowerScale and VAST across cloud, edge, and air-gapped environments, including K0rdent, Cluster API, Harbor, and PKI/TLS infrastructure.

Build and maintain Go backend microservices for Mirantis’ multi-tenant GPU infrastructure control plane. Responsibilities include designing REST APIs and database schemas, implementing Temporal workflows and event-driven services, managing authentication and authorization, writing comprehensive tests, instrumenting production services, and packaging deployments with Docker, Helm, and Kubernetes. The role also involves code reviews, incident debugging, and cross-regional collaboration.

Provides department-wide technical direction for k0rdent across Kubernetes, AI infrastructure, AI applications, and observability. Designs cross-cutting systems, establishes engineering standards, resolves architectural risks, mentors Staff and Principal engineers, and aligns product strategy with durable technical execution. The role also engages customers, partners, upstream communities, and industry forums while contributing code and prototypes to solve complex infrastructure problems.

Design and implement infrastructure services for a GPU-as-a-Service platform. Build REST and gRPC APIs, bare-metal provisioning workflows, Kubernetes cluster automation, reconciliation loops, and durable asynchronous operations. Manage server enrollment, inspection, OS provisioning, cluster creation, hardware inventory interfaces, error handling, idempotency, and multi-tenant infrastructure reliability.

Design and develop Rust and Go control-plane microservices, Kubernetes operators, reconciliation engines, and APIs for bare-metal AI infrastructure. Integrate datacenter networking systems, DPUs, network operating systems, and hardware-management platforms. Build observability with OpenTelemetry, troubleshoot distributed systems, and maintain rigorous testing practices. The role requires expertise in datacenter networking protocols, Linux networking, Kubernetes, provisioning, security, virtualization, and high-performance interconnects, along with architectural documentation and open-source collaboration.

Own the vision, roadmap, backlog, and priorities for k0rdent AI observability across GPU infrastructure and distributed AI workloads. Define integrations for metrics, tracing, logs, telemetry, and alerting across Kubernetes, networking, storage, schedulers, inference platforms, and databases. Partner with engineering, marketing, field teams, customers, and ecosystem vendors to shape requirements, evaluate trade-offs, develop positioning, and support deployments.

Deploys, integrates, operates, and tunes high-performance NFS storage for Kubernetes, GPU, and AI workloads. Responsibilities include CSI integration, Linux and network optimization, storage lifecycle management, air-gapped platform support, infrastructure-as-code, GitOps automation, observability, and troubleshooting distributed storage performance and reliability across hybrid, edge, and bare-metal environments.