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Senior Software Engineer, AIOps

NVIDIA· Engineer, Sys SW
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Raanana, Israel, Tel Aviv, IsraelPosted 2w ago

About the role

Senior software engineer for the AIOps platform, building distributed systems to ingest telemetry from GPU clusters, deploy and monitor predictive AI models, and enable real-time observability and automated diagnostics in both SaaS and on-prem environments.

Responsibilities

  • Architect and build an agentic AIOps system that autonomously monitors GPU fleet health, aggregates and correlates massive telemetry streams, surfaces intelligent alerts, and orchestrates multi-step diagnostic workflows and corrective actions - powering real-time dashboards, automated root-cause analysis, and proactive incident response.
  • Research, evaluate, and prototype data storage strategies and data representations across diverse database technologies and modalities, ensuring AI models are trained on high-quality, well-structured data that improves predictive accuracy and generalization.
  • High-Scale Engineering: Design distributed systems to handle the extreme telemetry density of large-scale AI clusters, ensuring efficient data ingestion, processing, and real-time analysis.
  • Instrument services with deep observability (metrics, logs, traces) to support rapid debugging and continuous performance improvement.
  • Build and own the model-serving infrastructure that operationalizes predictive algorithms at scale - packaging, versioning, deploying, and monitoring AI models in both SaaS and on-premises environments.
  • Contribute to the platform's core libraries and abstractions that accelerate development across the broader AIOps engineering team.

Qualifications

  • B.Sc./M.Sc. in Computer Science, Computer Engineering, or a related technical field.
  • 8+ years of software engineering experience building production distributed systems.
  • Core Systems Programming: Expert-level proficiency in languages such as Go, C++, or Rust, with a focus on high-performance, concurrent architectures.
  • Solid understanding of Kubernetes and container-based deployments for production services.
  • Experience deploying, monitoring, and maintaining ML models or data-intensive services in a production environment.
  • Comfort working in ambiguous, fast-moving environments where the product is still being shaped.

Skills

Required:Distributed systems

Benefits

  • Competitive salaries
  • Generous benefits package
Last updated Oct 9, 2026. Interested? Apply on the company site.

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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