2 days ago
Base Salary
$184k - $357k/yr
Responsibilities
- Build self-service SDKs, workflow templates, reference implementations, and catalogs of reusable agents, tools, and connectors.
- Translate operational intent into versioned, testable policies covering triggers, approvals, maintenance windows, capacity limits, recovery paths, and blocking conditions.
- Define common contracts and compatibility standards for tools, state, events, and workflow execution, and guide migrations to shared services.
- Build agents that analyze hardware diagnostics, logs, metrics, topology, configuration, and incident history to produce evidence-backed diagnoses and executable remediation plans.
- Enforce authorization, action histories, human review, bounded retries, cancellation, and compensating actions for automated operations.
- Automate provisioning validation, node quarantine, workload-aware maintenance, repair, upgrades, and return to service using Kubernetes, fleet-management systems, schedulers, and hardware interfaces.
- Solve fleet-scale distributed-systems problems involving partial failures, duplicate events, stale state, conflicting remediations, noisy telemetry, and control-plane bottlenecks.
- Establish shared evaluation, CI/CD, staged rollout, and observability capabilities across teams.
- Drive adoption through architecture and build reviews, migration plans, documentation, hands-on partnership, and cross-functional alignment.
Requirements
- 8+ years of experience in software engineering or a related field.
- Bachelor of Science in Computer Science, Engineering, Physics, Mathematics, or a comparable field, or equivalent experience.
- Expert-level knowledge of a systems programming language such as Go, Python, and/or Rust, with a solid understanding of data structures and algorithms.
- Strong background in Linux system administration and management.
- Experience with cluster orchestration tools including Kubernetes and/or SLURM.
- Understanding of software-development patterns for agents and current security practices for agentic systems.
- Understanding of performance, security, and reliability in complex distributed systems, including architecture, data synchronization, fault tolerance, and state management.
- Preferred qualifications include open-source project governance, provider-independent large-scale distributed systems, datacenter operations, GPU hardware, advanced Kubernetes or SLURM experience, and Machine Learning Operations, training, and/or security experience.
Benefits
- Hybrid work arrangement indicated by the #LI-Hybrid designation.
- Eligible for equity and benefits.
- Applications accepted at least until November 14, 2026.
- The posting is for an existing vacancy.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.