Software Engineer Jobs in San Jose, CA

Design, build, and own full-stack web and mobile applications and backend infrastructure. Architect scalable APIs, databases, and orchestration services, integrate and productize ML/AI models, collaborate with design and data science, and drive the software lifecycle from prototype to production.

Design, build, and scale agentic AI platforms using LLMs, RAG, and multi-agent frameworks. Integrate agents with enterprise data, microservices, and ServiceNow. Ensure reliability, observability, and guardrails, mentor engineers, and collaborate with Cloud and AI teams to deliver production-grade autonomous systems.

The Staff Software Engineer will lead the development of cloud-native AI platforms, optimizing AI workload deployment in Kubernetes environments and collaborating with cross-functional teams.

Design, build, and deliver an AI and machine learning platform, enhancing developer velocity while collaborating with cross-functional teams.

Develop and implement testing frameworks for a Big Data platform, ensure quality through unit tests, and lead end-to-end testing initiatives.

Design and build next-generation autonomous vehicle systems spanning prediction, decision, planning, and control. Integrate classical safety stacks with large-scale AI foundation models and inference architectures. Develop world-model based planning, end-to-end driving pipelines, system-level safety and fallback strategies, and production-grade AV software from perception through control.

Serve as technical lead between NVIDIA and hyperscale CSPs on GPU firmware and system software. Drive firmware update orchestration, recovery procedures, multi-GPU coordination, telemetry/health monitoring, and incorporate CSP feedback into NVIDIAs roadmap to improve fleet-scale manageability and reliability.

Design and implement idiomatic, safe Rust libraries and APIs for CUDA GPU computing; build Rust abstractions over native C/C++ interfaces; develop and maintain supporting C/C++ components; ensure FFI and Python interoperability; optimize cross-language and GPU performance; own features end-to-end including testing, profiling, benchmarking, documentation, packaging, and maintenance; collaborate with compiler, runtime, and Python teams; investigate and resolve safety, correctness, compatibility, and performance issues.

Develop core components of the CUTLASS platform, contribute to the MLIR-based backend compiler stack, and author example kernels while collaborating with GPU architecture teams.

Lead technical engagements with cloud service providers on rack-scale system software and firmware. Drive architecture alignment, integration readiness, error handling and recovery, health telemetry, firmware orchestration, and serviceability. Capture CSP feedback, influence NVIDIA system software design, improve tooling and tests, and mitigate execution risks through early collaboration.

Serve as NVIDIA's CSP-facing principal for end-to-end performance: drive characterization with hyperscaler engineering teams, gather and synthesize workload feedback, prioritize optimizations across CUDA/NCCL/driver/firmware, validate benchmarks and tools, update stress/profiling tooling, define test strategies, and ensure performance integration and acceptance for customer-representative configurations.

The role involves benchmarking deep learning models on NVIDIA GPUs, improving software performance, and developing automation tools for performance optimization.

Design and build simulation environments for integrated labs, HILs, and software benches; own lab tools and interfaces ensuring configuration management and traceability for certification; integrate third-party hardware/software; develop CI/CD-enabled simulation pipelines; and provide technical guidance, cross-functional troubleshooting, and standards contributions.

Design, build, test, and deploy integration, diagnostic, and automation tools and agents for DPU-based platforms. Lead test planning and execution, manage field incidents, maintain dashboards and KPIs, drive cross-functional debugging, and feed learnings back into engineering to improve reliability and releases.

Lead design and implementation of security systems and controls for large-scale AI and HPC cluster infrastructure. Drive incident response, risk assessment, system hardening, governance, audit readiness, and cross-team collaboration to protect hardware, software, and datacenter platforms.

Lead design and implementation of secure, scalable policy and platform software across cloud and hybrid environments. Drive technical strategy, mentor senior engineers, influence architecture and standards, and collaborate across product and business teams to deliver long-term, reliable security solutions.

Lead architecture and implementation of low-latency IPC middleware, compiler/toolchain infrastructure, and deterministic simulation platforms. Own build systems, distributed caching, crash triage tooling, and performance/memory optimization across embedded autonomy stacks. Provide technical leadership, mentoring, and cross-team standards to improve developer velocity and system reliability.

Design and build AI-driven developer experience tooling: implement rapid-feedback loops, predictive models for risky commits and build failures, AI agents to select tests, and CI pipeline automation. Measure developer productivity metrics, improve cycle time and MTTR, and reduce systemic friction across the software development lifecycle.

Design, develop, and deliver control software and firmware for ultra high-performance, multi-processor embedded products. Own full product lifecycle from bring-up to production, perform debugging and testing, support customer trials and field issues, collaborate cross-functionally, and provide technical leadership to small teams.

Build and maintain infrastructure automation, integrations, and SRE tooling. Develop backend services, infrastructure-as-code, observability, and provisioning for bare metal, VMs, and Kubernetes. Collaborate with hardware, software, and AI teams, drive operational excellence, and provide technical leadership.

Design, implement, and enhance cloud backend services for Netskope Client; build high-throughput, scalable APIs; deploy and manage containerized workloads on Kubernetes; collaborate with product, QA, and stakeholders; write tests, debug distributed systems, and ensure reliability, scalability, and observability for cloud security solutions.

Join a talent network connecting principal front-end, back-end, and full-stack engineers with VC-backed startups. Responsibilities include driving technical architecture, building scalable full-stack applications, designing APIs and cloud-native services, optimizing performance and reliability, leading deployment and CI/CD best practices, and mentoring senior engineers while aligning technical decisions with product and business goals.

Lead and build internal information systems platforms and tools. Hands-on full‑stack development, own end-to-end delivery, define architecture and technology choices, align roadmaps with mission needs, define metrics, and collaborate across teams to automate manual tasks and improve operations.

Lead architecture, design, development, integration, and testing of flight and embedded software for satellites. Implement drivers, platform services, RTOS-based applications on ARM Cortex-M, integrate hardware, define standards, enable testing strategies, and mentor senior engineers.

Lead development and maintenance of software test infrastructure, including hardware testbeds and simulated test scenarios. Implement CI/CD-driven testing, integrate simulation tools, expand off-nominal test coverage, mentor engineers, and coordinate cross-team testing policy and planning to improve release velocity and mission success.