Senior Engineering Manager, Object Storage - DGX Cloud

About the role

The Object Storage Platform team builds and operates NVIDIA's internal S3-compatible distributed object storage service, which is a critical part of the company's AI infrastructure. This platform stores, manages, and serves exabytes of data across various environments, supporting AI research and engineering.

Responsibilities

• 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, working closely with internal customers, Product Management, and Architecture to plan and deliver production services at scale.
• 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: Service Level Objectives (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.
• Promote 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.

Requirements

• 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.
• 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.

Qualifications

• 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.
• History of growing engineers into senior ICs or leads, and building diverse, inclusive teams with strong retention.

Skills

• Leadership and management skills.
• Technical expertise in distributed storage systems and cloud data services.
• Experience with S3-compatible object storage systems.
• Strong communication and collaboration skills.
• Ability to manage multiple projects and priorities simultaneously.
• Experience with AI-assisted development tools.

Benefits

NVIDIA offers a competitive compensation package, including base salary, equity, and benefits. The base salary range for this position is $272,000 - $431,250 for Level 4, and $320,000 - $488,750 for Level 5. Additional benefits may include health insurance, retirement plans, and paid time off.

Pay

Base salary will be determined based on your location, experience, and the pay of employees in similar positions.

Schedule

This is a full-time position.