Top Tech Jobs & Startup Jobs in Charlotte, NC

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 validate networking architectures for large-scale GPU clusters and AI infrastructure. Responsibilities include InfiniBand and RoCEv2 fabrics, multi-tenant networking, Linux host networking, Kubernetes and KubeVirt networking, automation, benchmarking, research, customer proofs of concept, technical documentation, partner collaboration, and conference presentations.

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.

Own end-to-end US recruiting for technical and business roles, including sourcing, pipeline development, hiring-manager advising, candidate experience, and closing. Recruiters will support engineering, product, account executive, pre-sales architect, and other go-to-market hiring. The role requires independent management of multiple searches, talent-market research, ATS administration in SmartRecruiters, and collaboration across distributed teams and time zones.

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.