Principal Software Engineer, AIOps

NVIDIA is powering the world’s most advanced AI Factories. To ensure their seamless operation, we are building a mission-critical Observability and Prediction platform. This platform is delivered as a dual-delivery model: both as a high-scale SaaS solution and as a robust on-premises deployment for our largest enterprise customers.

We are looking for a Principal Engineer to lead the architectural vision of the platform’s core. In this role, you will be the internal technical authority responsible for building a unified, high-performance engine that processes massive telemetry streams and runs advanced predictive models, regardless of where the infrastructure resides.

What You’ll Be Doing

• Unified Architectural Vision: Lead the design of a flexible, high-scale architecture that supports both multi-tenant SaaS environments and complex on-premises deployments.
• Operationalizing Predictive Models: Bridge the gap between AI research and production by architecting the framework that runs sophisticated predictive algorithms at scale, ensuring they are robust enough for mission-critical environments.
• 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.
• Cross-Organizational Leadership: Collaborate with networking and infrastructure teams to define the technical standards that enable the AIOps platform to integrate seamlessly with global AI infrastructure.
• Technical Excellence: Drive the engineering roadmap, mentor senior staff, and serve as the final authority on architectural decisions, ensuring the platform meets the highest standards of reliability and scalability.
  
  

• Education: B.Sc./M.Sc. in Computer Science, Computer Engineering, or a related technical field.
• Experience: 12+ years of experience in software engineering, with a proven track record of architecting complex, high-scale products delivered via SaaS and/or on-premises enterprise models.
• Architectural Sovereignty: Deep expertise in building environment-agnostic distributed systems, using technologies like Kubernetes to ensure portability across cloud and private data centers.
• Core Systems Programming: Expert-level proficiency in languages such as Go, C++, or Rust, with a focus on high-performance, concurrent architectures.
• Data Infrastructure: Extensive experience with high-throughput data processing (e.g., Apache Kafka) and managing large-scale telemetry or time-series data.
  
  

• The "0 to 1" Mindset: A proven track record of taking a complex architectural concept from a whiteboard to a stabilized, production-grade platform.
• A "Systems" Thinker: You don't just write software; you understand the full stack, from how data moves across the wire to how it’s processed in a distributed cluster.
• Infrastructure Evangelist: Experience in leading large-scale technical migrations or introducing modern engineering paradigms (like Cloud-Native or GitOps) into complex, high-stakes environments.
• Practical Innovation: The ability to simplify complex problems and build internal tools or frameworks that empower other engineering teams to move faster.