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Senior Staff Engineer - Employee Productivity

NVIDIA· Engineer, SW
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Santa Clara, CA$200k - $322kfull-timePosted 1mo ago

About the role

Senior Software Engineer focused on delivering AI-powered employee experiences across web and mobile, embedding LLM and vector-search capabilities, and leading system design, security, and observability to enable a scalable, secure, and accessible employee productivity platform.

Responsibilities

  • Build end-to-end features that power a seamless, AI-rich employee experience across web and native mobile apps.
  • Architect highly performant services and UIs that surface personalized content, knowledge, and search results to a global workforce.
  • Embed LLM and vector-search capabilities into existing product surfaces, driving relevance and continuous learning loops.
  • Own system design and code reviews raising the engineering bar and mentoring engineers across the team.
  • Integrate third-party HRIS, collaboration, and productivity platforms to create cohesive, automated user journeys.
  • Champion modern front-end patterns (React/Next.js, TypeScript, Tailwind) and cloud-native back-end practices (K8s, containers, CI/CD).
  • Instrument robust observability—tracing, structured logging, and SLA dashboards, helping our SREs achieve 24×7 reliability for employees in every region.
  • Uphold security, privacy, and accessibility standards across all user journeys and promote exceptional technical documentation and knowledge-sharing sessions that multiply the team’s velocity and quality.

Qualifications

  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience)
  • 12+ years of full-stack product engineering, including 3+ years at the principal or staff level guiding cross-functional teams.
  • Proven track record delivering consumer-grade web and/or mobile experiences at scale.
  • Expertise in search, recommendation, or applied-AI systems.
  • Hands-on experience with modern cloud infrastructure, K8s, and automated CI/CD.
  • Strong data-modeling with relational and NoSQL stores.
  • Fluency in application security.
  • Strong mentoring skills, with the ability to provide vision and contribute directly to implementation.

Skills

Required:Full-stack product engineeringLLM integrationCloud infrastructure (Kubernetes, containers, CI/CD)Data modeling (relational and NoSQL)SecurityMentoring

Benefits

  • equity
  • benefits (see NVIDIA benefits)
Last updated Sep 18, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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