Top Tech Jobs & Startup Jobs in Seattle, WA

Builds secure AI and agentic cybersecurity tooling, transforming research prototypes into production-ready services. Responsibilities include developing backend services, APIs, CLI tools, automation, and integration patterns; defining MVPs for ambiguous security and identity challenges; collaborating across research, product, enterprise security, and platform teams; and applying offensive security and adversarial thinking to address AI-specific risks such as injection, tool misuse, unauthorized access, data exfiltration, and unsafe delegation.

Leads software engineering teams delivering rack-scale infrastructure software, including control planes, lifecycle orchestration, system health, recovery, and fleet-scale reliability. Owns planning, staffing, releases, quality, production support, open-source delivery, and cross-functional coordination across hardware, firmware, networking, security, operations, customers, and partners. Builds technical leadership, manages engineering performance, and guides architecture and software quality.

Develop and implement core firmware features for Mellanox NICs supporting cloud, HPC, and storage networking. Collaborate with architecture and software teams, create verification tests, debug complex hardware/software systems, and contribute to firmware maintenance, qualification, and releases. The role requires strong C/C++ development, networking knowledge, PCIe and virtualization experience, scripting skills, and familiarity with distributed, high-performance computing environments.

Lead the architecture and development of scalable APIs, control planes, workflow orchestration, and fleet lifecycle automation for NVIDIA DGX Cloud. Drive integration across cloud systems, Kubernetes, Slurm, and observability platforms while improving reliability and reducing manual operations. Provide technical leadership, mentor senior engineers, influence organizational strategy, and deliver high-scale distributed infrastructure for AI and cloud computing.

Develop and deploy scalable AI, machine learning, deep learning, and data analytics solutions on cloud GPU platforms. Build customer proofs of concept using NVIDIA hardware and software, collaborate with cloud providers and sales teams, present technical solutions, support customer roadmaps, and resolve technical issues. Requires solutions or sales engineering experience, cloud deployment expertise, ML frameworks, GPUs, CUDA, DevOps/MLOps technologies, scripting, and strong communication skills.

Lead large-scale cloud infrastructure programs for NVIDIA DGX Cloud, partnering with cloud service providers and internal engineering teams to bring up global AI capacity. Define technical requirements, roadmaps, milestones, KPIs, and operational processes across compute, storage, networking, and GPU infrastructure. Manage capacity operations, risks, partner alignment, infrastructure deployments, compliance, security, and observability while driving continuous improvement and executive communication.

Develop CUDA compiler front-end capabilities, including language features, diagnostics, semantic analysis, and code generation. Improve compiler feedback for developers and AI agents, track evolving C++ standards, and contribute across LLVM optimization, code generation, and MLIR. Collaborate with compiler, library, and developer tools teams to deliver robust production software.

Lead technical solution integration for strategic customers, cloud providers, and hyperscalers using NVIDIA AI infrastructure. Develop and deploy compute and networking solutions, support customer proofs of concept, conduct technical workshops and performance debugging, and advise business and engineering teams on product strategy. The role requires deep expertise in AI data-center networking, GPUs, InfiniBand, Ethernet, PCIe, switches, hosts, optics, and rack-scale infrastructure.

Design and guide security architecture for NVIDIA networking firmware and embedded subsystems. Responsibilities include threat modeling, analyzing firmware and hardware interactions, defining lifecycle security features, translating threats into requirements, partnering with hardware architects, and driving secure firmware development practices such as memory-safe C, static analysis, and fuzzing. The role requires expertise in firmware security, authorization models, cryptography, secure boot, attestation, and embedded systems.

Develop and optimize the open-source Triton compiler for high-performance AI workloads on NVIDIA GPUs. Design compiler technology using MLIR, generate efficient low-level GPU code, tune kernels with inline PTX, analyze hardware architectures, and optimize advanced AI algorithms and numerics. Collaborate with hardware architects and CUDA compiler teams while applying parallel programming, computer architecture, assembly, and performance debugging expertise.