Senior Engineering Manager, Object Storage - DGX Cloud

NVIDIA AI; Santa Clara (CA); On-site; USD 272,000 - 488,750; Full time

Job summary

NVIDIA is seeking a senior leader to build and run the Object Storage Platform organization. You will own the roadmap for the internal S3-compatible storage service, drive performance, reliability, and scale for AI workloads, and manage data movement tooling to keep GPUs fed with data.

You will recruit and mentor engineers, shape standards, and partner with SRE, Platform, and Security teams for smooth production transitions. Equity and benefits are included.

Qualifications

• BS, MS, or PhD in Computer Science, Electrical Engineering, or related field or equivalent experience.
• 10+ years of software engineering experience, including 4+ years in an engineering management role.
• Deep background in distributed storage systems or large-scale cloud data services.
• Hands-on development in Go, C++, Python, or equivalent.
• Experience building or scaling S3-compatible storage in production.
• Proven track record delivering production software on time.

Responsibilities

• Lead and grow a multi-team engineering organization with a focus on quality, reliability, and culture.
• Own roadmap execution for the internal S3-compatible storage service with stakeholders.
• Drive development and operation to meet performance, durability, and scalability goals at exabyte scale.
• Manage Data Movement Tools to stage datasets and artifacts efficiently.
• Define service reliability standards, capacity planning, and incident response with SRE alignment.
• Enforce engineering standards, CI/CD, testing, observability, and production readiness.
• Recruit, mentor, and develop engineers; conduct regular performance and growth conversations.
• Collaborate with SRE, Platform, Networking, and Security teams for smooth transitions to production.
• Champion AI-assisted development tooling to boost productivity and report status to leadership.

Skills

Go

C++

Python

Distributed storage

Leadership

Education

BS/MS/PhD in CS/EE or related field

Tools

CI/CD pipelines

Production observability

Job description

Job Requisition ID: JR2021079

Job Category: Engineering

Time Type: Full time

NVIDIA's Object Storage Platform team builds and operates the company's internal S3-compatible distributed object storage service — a critical piece of infrastructure that stores, manages, and serves exabytes of data across NVIDIA's on-premises and hybrid environments. This platform is the storage backbone for NVIDIA's AI infrastructure, enabling researchers and engineers to reliably store massive datasets, model checkpoints, and training artifacts at scale. A companion data movement team extends the platform with tooling that efficiently stages and moves data closer to GPU clusters, minimizing idle accelerator time and accelerating training and inference pipelines.

What You’ll Be Doing

• Lead and grow a multi-team engineering organization, setting a high bar for software quality, service reliability, and engineering culture.
• Own roadmap execution for NVIDIA’s internal object storage service — partnering with internal customers, Product Management, and Architecture to translate multi-quarter goals into clear engineering plans with measurable milestones.
• Drive development and operation of NVIDIA’s S3-compatible object storage service, ensuring it meets the performance, durability, availability, and scalability demands of AI training and inference workloads at exabyte scale.
• Lead the Data Movement Tools team in building and evolving tooling that stages datasets, model checkpoints, and artifacts from distributed storage to GPU-adjacent compute — minimizing I/O bottlenecks and keeping accelerators fully utilized.
• Define and uphold service reliability standards: SLOs, capacity planning, incident response, root cause analysis, and on-call hygiene. Partner with SRE to ensure the platform meets the availability commitments internal customers depend on.
• Establish and enforce engineering standards across both teams: design reviews, code quality, CI/CD practices, automated testing, and production observability. Recruit, mentor, and develop engineers across all levels, conducting regular 1:1s, performance cycles, and career growth conversations. Build a diverse, inclusive, and high-retention team.
• Collaborate closely with SRE, Platform, Networking, and Security teams to ensure smooth transitions from development to production and rapid resolution of customer-impacting issues.
• Champion the adoption of AI-assisted development tooling — coding assistants, agentic workflows, and automated testing harnesses — to accelerate team productivity and raise engineering output. Represent the Object Storage engineering organization to senior leadership, providing transparent status updates, surfacing risks early, and advocating for the resources needed to succeed.

What We Need To See

• BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field — or equivalent experience.
• 10+ overall years of software engineering experience, including 4+ years in an engineering management role leading teams of 10 or more engineers delivering production services at scale.
• Deep technical background in distributed storage systems, object storage platforms, or large-scale cloud data services; hands-on development experience in Go, C++, Python, or equivalent systems languages.
• Direct, hands-on experience building or scaling S3-compatible object storage systems in a production cloud or private cloud environment — with demonstrable improvements in throughput, durability, or operational efficiency.
• Demonstrated experience building or operating cloud storage services — with accountability for reliability, performance, and capacity at scale in a production environment.
• Proven track record of shipping production software on time — managing scope, risk, and delivery across multiple concurrent workstreams.
• Strong experience with modern software development and service delivery practices: CI/CD, automated testing, SLO-based reliability, production observability, and incident management.
• Demonstrated ability to attract, develop, and retain strong engineering talent in a driven environment, with a track record of growing engineers into senior and staff-level roles.
• Excellent written and verbal communication — able to translate complex technical trade-offs for product partners and engineering constraints for executive audiences.

Ways To Stand Out From The Crowd

• Prior experience designing and operating internal cloud storage services (IaaS/PaaS) with well-defined SLAs, metered usage, and internal customer-facing APIs.
• Background in data movement, data staging, or prefetching tooling for AI/ML workloads — with direct experience optimizing data pipelines to reduce GPU idle time during training or inference.
• Familiarity with AI infrastructure storage patterns: checkpoint storage, dataset versioning, write-once-read-many (WORM) access patterns, or storage-aware scheduling at 10k+ GPU scale. Experience managing capacity planning, cost optimization, and chargeback modeling for shared internal storage infrastructure.
• Track record of adopting AI-assisted development tools to meaningfully improve team productivity, with concrete examples. History of growing engineers into senior ICs or leads, and building diverse, inclusive teams with strong retention.

NVIDIA’s Object Storage Platform and data movement tooling form a critical layer in keeping NVIDIA’s GPU fleet productive — every model trained, every checkpoint saved, and every dataset staged passes through the systems this team builds and operates. This is a high-impact role at the center of NVIDIA’s AI infrastructure.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD for Level 4, and 320,000 USD - 488,750 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 21, 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.