Senior Cloud Software Engineer, DGXC Data Services at Nvidia

Job description

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: • Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access. • Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows. • Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems. • Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale. • Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification. What we need to see: • BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience. • Strong foundation in algorithms, data structures, distributed systems, and practical software design. • Experience building, shipping, and operating backend or cloud-native services using Kubernetes, cloud providers such as AWS, GCP, or Azure, and languages such as Go, Python, Rust, C/C++, or Java. • Ability to design APIs, document systems, reason through tradeoffs, communicate clearly, and break ambiguous problems into practical execution plans. • Experience working across engineering, product, platform, and operations teams to deliver reliable production software. • Curiosity and practical judgment around AI-assisted or agentic engineering workflows, including using clear intent, specifications, acceptance criteria, tests, and verification to guide development. Ways to stand out from the crowd: • Hands-on experience building, scaling, or operating large-scale data, storage, or ML infrastructure services. • Experience solving enterprise-grade data management, governance, analytics, or AI workflow problems with modern data and ML infrastructure technologies. • Strong background in distributed systems, storage systems, cloud infrastructure, performance engineering, observability, or agentic engineering practices. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention, the GPU, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until September 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access.
Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows.
Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems.
Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale.
Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification.
BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience.
Strong foundation in algorithms, data structures, distributed systems, and practical software design.
Experience building, shipping, and operating backend or cloud-native services using Kubernetes, cloud providers such as AWS, GCP, or Azure, and languages such as Go, Python, Rust, C/C++, or Java.
Ability to design APIs, document systems, reason through tradeoffs, communicate clearly, and break ambiguous problems into practical execution plans.
Experience working across engineering, product, platform, and operations teams to deliver reliable production software.
Curiosity and practical judgment around AI-assisted or agentic engineering workflows, including using clear intent, specifications, acceptance criteria, tests, and verification to guide development.
Hands-on experience building, scaling, or operating large-scale data, storage, or ML infrastructure services.
Experience solving enterprise-grade data management, governance, analytics, or AI workflow problems with modern data and ML infrastructure technologies.
Strong background in distributed systems, storage systems, cloud infrastructure, performance engineering, observability, or agentic engineering practices.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until September 18, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aikubernetesawsgcpazuregopythonrustjavaml

Platform: eightfold
Effort: medium