Senior Engineering Manager, Object Storage - DGX Cloud

NVIDIA•Us, CO

About The Position

NVIDIA is hiring a Senior Engineering Manager to lead the Object Storage Platform team, which builds and operates the company’s internal S3-compatible distributed object storage service. This service stores, manages, and serves exabytes of data across NVIDIA’s on-premises and hybrid environments, supporting AI infrastructure workloads such as datasets, model checkpoints, and training artifacts. The manager will lead the team’s development and site reliability engineering responsibilities and own the full software development and service delivery lifecycle, from roadmap planning through production operations. The role combines technical direction, operational accountability, team development, and cross-functional collaboration to ensure the storage platform delivers the performance, durability, availability, and scalability required by AI training and inference workloads. The position works closely with internal customers, Product Management, Architecture, Data Movement, GPU compute, Platform, Networking, Security, and global SRE teams. The manager will also represent the organization to senior leadership and champion AI-assisted development tools. The expected base salary range is USD 272,000–431,250, with eligibility for equity and benefits. Applications will be accepted at least until November 8, 2026.

Requirements

BS, MS, or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
10+ years of overall software engineering experience.
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.
Experience building or operating production cloud storage services, with accountability for reliability, performance, and capacity at scale.
Track record of shipping production software on time and managing scope, risk, and delivery across multiple concurrent workstreams.
Strong experience with CI/CD, automated testing, SLO-based reliability, production observability, and incident management.
Ability to attract, develop, and retain strong engineering talent, including growing engineers into senior and staff-level roles.
Excellent written and verbal communication skills, including the ability to explain technical trade-offs to product partners and engineering constraints to executive audiences.

Nice To Haves

Experience designing and operating internal cloud storage services (IaaS/PaaS) with defined SLAs, metered usage, and internal customer-facing APIs.
Background in observability and system reliability engineering for distributed systems.
Familiarity with AI infrastructure storage patterns, such as 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.
Examples of adopting AI-assisted development tools to meaningfully improve team productivity.
History of growing engineers into senior individual contributor or lead roles and building diverse, inclusive teams with strong retention.

Responsibilities

Lead and grow an engineering organization, setting standards for software quality, service reliability, and engineering culture.
Own roadmap execution for NVIDIA’s internal object storage service, translating multi-quarter goals into engineering plans and measurable milestones with internal customers, Product Management, and Architecture.
Drive development and operation of the S3-compatible object storage service to meet the performance, durability, availability, and scalability demands of AI workloads at exabyte scale.
Collaborate with Data Movement and GPU compute teams to identify and minimize I/O bottlenecks and keep accelerators fully utilized.
Define and uphold service reliability standards, including SLOs, capacity planning, incident response, root cause analysis, and on-call hygiene.
Partner with global SRE teams to ensure 24/7 service availability and operability.
Establish and enforce engineering standards for design reviews, code quality, CI/CD, automated testing, and production observability.
Recruit, mentor, and develop engineers at all levels; conduct regular 1:1s, performance cycles, and career-growth conversations.
Build a diverse, inclusive, high-retention team.
Collaborate with Platform, Networking, Security, and global SRE teams to support transitions from development to production and resolve customer-impacting issues rapidly.
Champion AI-assisted development tooling, including coding assistants, agentic workflows, and automated testing harnesses, to improve productivity and engineering output.
Represent the Object Storage engineering organization to senior leadership, provide transparent status updates, surface risks early, and advocate for needed resources.
Manage scope, risk, and delivery across concurrent workstreams to ship production software on time.