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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.

Build and own a multi-tenant web platform for managing AI infrastructure. Develop Next.js and React features, server-side authentication and API proxying, generated TypeScript SDKs, resilient data synchronization, design-system components, accessibility, performance, testing, observability, and production deployment. Collaborate with backend and globally distributed teams, review code, troubleshoot production issues, and mentor junior engineers.

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.

Design and build enterprise LLM-serving infrastructure on Kubernetes, including GPU scheduling, scaling, model lifecycle management, Helm packaging, offline deployments, platform integrations, and production observability. Contribute across a multi-service Go codebase, create design documentation, participate in reviews, and help guide engineering direction within an autonomous remote-first team.

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.

Deploy, integrate, operate, and optimize high-performance NFS storage for GPU-accelerated Kubernetes and AI platforms. Configure Linux storage and networking, integrate CSI storage into k0s and K0rdent clusters, automate provisioning through Terraform/OpenTofu and GitOps, and build observability for capacity, performance, and reliability. Diagnose end-to-end storage issues across hybrid, edge, and air-gapped environments while establishing operational standards.

Design and build Go-based control-plane services, CSI drivers, storage integrations, observability tools, and infrastructure automation for Kubernetes AI platforms. Integrate enterprise and scale-out storage, support bare-metal and hybrid provisioning, and deliver declarative Terraform/OpenTofu and GitOps workflows. Architect reliable storage solutions for Kubernetes clusters, air-gapped environments, and sovereign infrastructure, including artifact mirrors and PKI/TLS.

Own the vision, roadmap, backlog, and priorities for k0rdent AI storage across GPU clusters. Define capabilities for parallel file systems, object and block storage, tiering, snapshots, data protection, and GPU-optimized data paths. Translate customer requirements into product direction, partner with engineering on scalable storage features, develop positioning and field assets, support strategic accounts, and represent Mirantis with customers, analysts, and ecosystem partners.