Senior System Software Engineer - Data Platform Observability

Posted Yesterday
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2 Locations
In-Office or Remote
184K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Lead design and implementation of a scalable observability and data platform: high-performance telemetry ingestion, data governance and policy enforcement, modern UX/APIs, cost-optimized tiered storage, and automation for lifecycle and pipeline orchestration. Collaborate with cross-functional teams to provide operational and strategic data for debugging, performance, and reliability.
Summary Generated by Built In

NVIDIA’s Hardware Infrastructure organization is seeking a Senior System Software Engineer to lead the evolution of our next-generation Data & Observability Platform. We serve and collaborate directly with NVIDIA’s rapidly growing AI, HW, and SW engineering and research teams across the company. We are looking for a Full-Stack technical lead who is not afraid to dig deep into infrastructure. You will be the technical anchor for our Observability stack, driving the transition to a modern tooling that is best fit for our customers and use cases. You will build the centralized platform that thousands of NVIDIA engineers rely on to visualize chip telemetry, debug distributed pipelines, and ensure platform reliability.

What you’ll be doing:

  • Architect High-Performance Ingestion: Design and build centralized telemetry pipelines capable of handling massive scale. You will solve global latency challenges by implementing modern, push-based edge collection architectures to replace legacy proxy models.

  • Build Policy Enforcement Systems: Design and implement the technical infrastructure for data governance,  policy engines, access control enforcement points,  secure credential management, and audit logging. Looking for someone who has built governance controls into a platform, not just administered them.

  • Focus on User Experience: Develop a modern, web interface and APIs  that unify distinct observability signals into a seamless, consolidated user experience.

  • Optimize Storage & Cost: Implement cost-effective tiered storage architectures. You will define strategies for routing high-volume data to cold storage solutions to reduce costs while maintaining multi-year data retention.

  • Drive Platform Automation: Architect workflow orchestration systems to automate platform maintenance, data lifecycle management, and complex pipeline operations.

  • Work in a diverse team to provide operational and strategic data to empower our engineers and researchers to improve performance, productivity, and efficiency to continuously improve quality, workloads, and processes through better observability.

What we need to see:

  • BS or MS in Computer Science, Electrical Engineering, or related field (or equivalent experience).

  • 8+ years of full-stack software development experience with a focus on Data Platforms or Infrastructure Tools.

  • Strong Full-Stack Fluency: Proficiency in high-performance backend systems programming and modern frontend web frameworks for building responsive user interfaces (Python, JS, Java, Rust, Go, React, or similar).

  • Observability Expertise: Experience with observability platforms such as Apache Spark, Elastic/Open Search, Grafana, Prometheus, and other similar open-source tools. Hands-on experience operating and extending the Grafana Ecosystem or ELK stack at scale. You understand the internals of time-series databases and inverted indexes.

  • Infrastructure-as-Code: Experience deploying complex stateful services on Kubernetes using Helm, Terraform, or Ansible.

  • Streaming & Storage: Familiarity with event streaming and modern data lake formats 

Ways to stand out from the crowd:

  • Experience writing Custom Grafana data source Plugins or backend plugins in Go.

  • Background with migrating legacy monoliths to microservices or Vector-based pipelines.

  • Experience with OpenTelemetry (OTEL) collector configuration, writing custom processors, or instrumentation SDKs.

  • Background in Data Governance, including implementation of Policy-as-Code or compliance frameworks in a regulated environment.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 15, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • BS or MS in Computer Science, Electrical Engineering, or related field (or equivalent experience).
  • 8+ years of full-stack software development experience focused on Data Platforms or Infrastructure Tools.
  • Proficiency in high-performance backend systems programming and modern frontend frameworks (Python, JavaScript, Java, Rust, Go, React).
  • Experience with observability platforms (Apache Spark, Elastic/OpenSearch, Grafana, Prometheus, ELK); hands-on operating/extending Grafana or ELK at scale; understanding time-series DB internals and inverted indexes.
  • Experience deploying complex stateful services on Kubernetes using Helm, Terraform, or Ansible.
  • Familiarity with event streaming and modern data lake formats.
  • Experience writing custom Grafana data source or backend plugins in Go.
  • Experience migrating legacy monoliths to microservices or Vector-based pipelines.
  • Experience with OpenTelemetry collector configuration, custom processors, or instrumentation SDKs.
  • Background in Data Governance, including Policy-as-Code or compliance frameworks in regulated environments.

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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