Senior Full-Stack Lead Engineer

Details

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 30 years. Today, it is at the forefront of AI innovation, powering breakthroughs in research, autonomous vehicles, robotics, and more. The DGX Cloud team builds and operates the AI infrastructure that fuels this progress.

The AI Hub team within the DGX Cloud AI Infrastructure organization accelerates AI research by ensuring NVIDIA's AI infrastructure is used efficiently, transparently, and at scale. The team is building a unified, self-service "single pane of glass" portal that enables AI researchers to manage, monitor, and optimize their use of managed AI research superclusters.

Responsibilities

• Lead the architecture and delivery of high-scale web products across frontend, backend services, and data layers, with clear availability and latency targets, including SLOs and SLAs.
• Own multi-team initiatives end to end, including problem discovery, RFCs, design reviews, phased rollouts, and success metrics tied to product and business outcomes.
• Drive reliability, performance, and observability improvements to meet exascale standards.
• Establish engineering standards and reusable platforms and design systems to reduce complexity, support load, and long-term technical debt.
• Collaborate with NVIDIA AI Research teams to identify pain points and deliver the next-generation user experience that accelerates their work.
• Mentor and sponsor engineers, and improve code quality, testing, security, and observability through reviews, pairing, and coaching.
• Stay ahead of AI and machine learning infrastructure trends and drive adoption of best practices within the team.

Requirements

• 12 or more years of software engineering experience delivering production web systems.
• Bachelor's degree or higher in Computer Science or a related technical field, or equivalent experience.
• Strong cross-functional collaboration skills, including active listening, translating complex use cases into clear technical requirements, and designing data models aligned with business logic and outcomes.
• Deep cloud expertise with AWS, GCP, or Azure; infrastructure as code; containers and orchestration using Docker and Kubernetes; and mature CI/CD and safe deployment practices.
• Full-stack experience with modern single-page application frameworks such as React, Next.js, Vue, or Nuxt; JavaScript or TypeScript; and one or more backend languages, including Node.js, Python, or Golang.
• Familiarity with observability stacks such as OpenSearch, Prometheus, Grafana, or Loki.
• Proficiency in REST API design, schema evolution, and integration patterns, with a strong commitment to automated testing.
• Experience building machine learning platforms or self-service internal infrastructure tools focused on efficiency, resiliency, and observability.
• Clear written and verbal communication skills, strong problem-solving ability, and a growth mindset.
• Experience leveraging AI-assisted development tools such as Cursor.

Preferred Qualifications

• Hands-on machine learning platform depth, including machine learning engineering experience or strong familiarity with deep learning frameworks such as PyTorch, TensorFlow, or JAX, and distributed training ecosystems such as Ray.
• Datacenter-scale operational experience, including GPU cluster debugging, performance triage, and root-cause analysis across complex distributed systems.

Benefits

NVIDIA provides competitive salaries, equity, and a comprehensive benefits package. The company fosters a diverse and supportive environment and is an equal opportunity employer. NVIDIA also uses AI tools in its recruiting processes.

Applications for this job will be accepted at least until July 13, 2026. This posting is for an existing vacancy.