Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
Communication @ 7
Distributed Systems @ 7
GPU @ 4
HPC @ 4
LLM @ 6
Machine Learning
Networking @ 7
Observability @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is looking for a Senior Software System Architect to help shape networking management systems, AIOps platforms, and applied AI solutions for AI cluster operations. The role involves working with customers, internal operational teams, architects, Product, and Engineering to translate complex operational challenges into clear requirements and scalable architectures, and carry these capabilities through implementation and delivery into products that provide measurable customer value.
The ideal candidate has deep technical judgment, a broad systems perspective, and the persistence to move ideas into production while building alignment across teams.
Responsibilities
- Define architectures for management and intelligent automation capabilities spanning telemetry, observability, remediation, and operational automation.
- Engage customers, cluster operations teams, and compute authorities to understand their challenges and architect solutions that improve operational efficiency, reliability, and scalability.
- Partner with Product and Engineering to translate architectural recommendations into prioritized features and drive their inclusion in the Plan of Record (POR), defining requirements, dependencies, and success criteria.
- Resolve system tradeoffs across hardware, firmware, software, and data platforms, with attention to scale, reliability, performance, and usability.
- Guide design decisions through implementation, including hands-on development of targeted proofs of concept (PoCs) and technical investigations to validate critical assumptions.
- Provide strategic direction and system-level leadership across teams, guiding engineering choices and promoting sophisticated, AI-centered operating practices.
Requirements
- MSc. or higher in Computer Engineering or Computer Science, or equivalent experience.
- 8+ years of experience in system or software architecture, with a record of delivering sophisticated distributed systems in production.
- Hands-on experience architecting and delivering distributed software systems, including cloud-native services, deployment, and orchestration.
- Deep understanding of data center infrastructure across compute, networking, and management systems, including how these components interact at scale.
- Ability to connect the big picture with precise technical reasoning and recognize which details matter.
- Experience translating customer needs into system capabilities and influencing decisions across technical and product teams.
- Strong ownership, initiative, and follow-through, supported by clear technical writing and communication.
Preferred Qualifications
- Experience with AI factory infrastructure, large-scale GPU clusters, HPC, or distributed AI training and inference workloads.
- Hardware/software co-design experience spanning compute, networking, firmware, and software.
- Deep understanding of telemetry and observability platforms, including the application of AI/ML.
- Hands-on development of LLM agents, including orchestration, tool integration, context management, and evaluation.
- Contributions to open-source communities, particularly in AI infrastructure or observability.
Compensation
The expected base salary ranges are 101,250 EUR–175,500 EUR for Level 4 and 123,750 EUR–214,500 EUR for Level 5. Base salary is determined based on location, experience, and other objective job-related factors. NVIDIA also offers competitive salaries and a generous benefits package.