Top Tech Jobs & Startup Jobs in Austin, TX

Designs and optimizes NVIDIA AI and HPC infrastructure for energy-sector customers, including GPU clusters, networking, storage, orchestration, monitoring, security, and edge deployments. Partners with customers and internal teams on architecture reviews, proof-of-concepts, benchmarks, production deployments, reference architectures, and technical documentation. Advises on distributed training, inference, RAG, cluster reliability, and performance optimization while supporting strategic customer and partner engagements.

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.

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 engineering enablement for large-scale AI/HPC clusters, managing a support team, training and documentation, request intake and prioritization, specialist debugging coordination, and user community development. Partners across architecture, software, firmware, networking, storage, datacenter operations, performance, and program teams. Uses service metrics and user feedback to improve workflows, self-service guidance, resource allocation, and support quality.

Conduct novel research in AI security and cybersecurity, focusing on securing AI models, agents, systems, and infrastructure. Develop tools and processes to identify and remediate vulnerabilities, investigate adversarial machine learning, publish findings, and collaborate across NVIDIA. Present complex technical results to security, machine learning, and business audiences while contributing to secure software development and AI safety.

Design, develop, optimize, and debug C++ software for ultra-low-latency WebRTC streaming. Implement real-time transport, security, media, and congestion-control protocols; contribute to standards and protocol solutions; define streaming quality KPIs; and integrate software with platform, connectivity, automotive, and hardware systems.

Investigate, assess, and remediate vulnerabilities across NVIDIA data center platforms. Responsibilities include vulnerability triage, exploitability analysis, CVSS and CWE assessment, security fixes, regression testing, dependency updates, automation, and coordinated disclosure. The role also improves secure development lifecycle practices through threat modeling, security reviews, testing, and security automation while collaborating across distributed engineering teams.

Design and deploy AI networking platforms in customer data centers. Partner with customers on GPU, compute, storage, and fabric architecture; support infrastructure bring-up; troubleshoot InfiniBand, RoCE, Linux, NIC, and switching issues; conduct technical reviews; build proof-of-concepts; and translate customer requirements into product and engineering feedback. Collaborate with systems engineering, product management, and sales while supporting large-scale AI cluster deployments.

Develop and maintain automated integration and deployment for components in a Kubernetes-based software stack. Manage third-party dependencies, validate compatibility, maintain integration workflows, troubleshoot cross-component issues, and ensure compatibility with NVIDIA hardware. The role requires extensive Linux software development experience, Python proficiency, Kubernetes and container expertise, and collaboration with QA, CI/CD, development teams, and upstream projects.

Lead NVIDIA’s HPE Enterprise ecosystem growth strategy, driving adoption of accelerated computing across strategic industries. Build executive relationships, develop partnerships, manage pipelines, coordinate global go-to-market programs, support complex sales negotiations, and collaborate with sales, marketing, product, engineering, and channel teams. Shape product direction, demand generation, training, and multi-region initiatives to expand revenue and market leadership.