Top Tech Jobs & Startup Jobs in Charlotte, NC

Drive technical engagements for NVIDIA’s on-premises AI Factory solutions. Advise partners, OEMs, and enterprise customers; design and validate scalable architectures; support deployments and troubleshooting; enable adoption of NVIDIA platforms; and communicate customer needs to engineering and product teams. The role requires hands-on expertise across AI infrastructure, hardware, firmware, operating systems, cluster management, workload orchestration, and system integration.

Design, develop, verify, and maintain embedded system software and kernel drivers for NVIDIA Tegra ARM-based SoCs. Responsibilities include pre-silicon modeling, silicon bring-up, core OS enablement, hardware and software collaboration, unit testing, documentation, and system-level debugging. The engineer will also influence hardware architecture through design specifications and support next-generation SoC platforms.

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.

Develop core libraries and tools for scalable agentic applications. Responsibilities include optimizing agent frameworks and harnesses, benchmarking performance, improving latency and cost, integrating RAG systems and vector databases, supporting GPU workflows, designing cross-language APIs, debugging runtime internals, and collaborating with open-source communities. The role also involves building evaluations, observability, middleware, guardrails, and other systems that improve agent quality, developer productivity, and deployment reliability.

Develop and maintain graphics system software, user-mode drivers, platform code, APIs, and SDKs across GPU architectures and operating systems. Ensure backward and forward compatibility across driver releases, collaborate on graphics and deep learning technologies, and support next-generation GPU design, development, and validation.

Lead technical partnership with Alphabet teams to drive adoption and integration of NVIDIA libraries, models, and frameworks. Coordinate cross-functional engineering and GTM teams, resolve integration challenges, influence product roadmaps, and deliver joint solutions that accelerate partner workloads and developer adoption.

Leads multifunctional initiatives defining safety architectures and requirements for autonomous vehicles. Develops safety concepts and analysis supporting continuous software delivery, improves safety metrics and analysis tools, evaluates safety data, and communicates readiness results. Collaborates with perception, AI, motion planning, and architecture experts to ensure DRIVE products meet rigorous safety standards.

Develop and lead production software-defined networking for NVIDIA’s global GPU cloud infrastructure. Design multi-tenant control and data planes using Open vSwitch, OVN, OpenFlow, Kubernetes, C, and Go. Build networking services, plugins, automation, testing, observability, and reliability improvements. Lead architecture and code reviews, mentor engineers, support on-call operations, and resolve complex production incidents through diagnostics and source-level debugging.

Lead founding AI Safety & Security Engineering team, define harness architecture and engineering standards, drive Find/Validate/Patch roadmap, mentor engineers, and translate research into production-grade, secure ML systems.

Design, develop, test, and extend NVIDIA’s large-scale object storage platform. Responsibilities include improving availability, reliability, durability, fault tolerance, and performance across deployments exceeding 10,000 nodes and exabytes of data. The role also automates storage infrastructure provisioning, management, and monitoring; supports AI/ML research teams; owns product delivery through support; and contributes to open-source storage projects.