Senior Full-Stack Software Engineer – Verification Data and Visualization Platform
at Nvidia
USD 152,000-287,500 per year
Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Docker @ 4
ElasticSearch @ 4
Grafana @ 4
Kafka @ 4
Kubernetes @ 4
Redis @ 7
Kibana @ 4
TypeScript @ 7
Spark @ 4
Java @ 4
Algorithms @ 4
Data Structures @ 4
Distributed Systems @ 4
Flink @ 4
Spark Streaming @ 4
Hiring @ 4
Communication @ 4
JavaScript @ 7
Microservices @ 4
UI/UX @ 4
Debugging @ 4
LLM @ 4
OpenTelemetry @ 4
GPU @ 4
Observability @ 4
AI @ 4
Data Visualization @ 4
Agentic AI @ 4
Data Pipelines @ 4
LangChain @ 4
- 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 has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. The Hardware Infrastructure team is building the next-generation event-driven data and visualization platform to power NVIDIA's GPU development efforts. The platform supports real-time data processing, streaming analytics, scalable data-driven applications, and is used across the company for real-time tracking, AI agents development, anomaly detection, and debugging of complex hardware verification and data processing flows.
Responsibilities
- Modernize front-end applications to serve a large and diverse customer base with complex concerns.
- Participate in the full life-cycle of tool development: end-to-end environment troubleshooting, testing, and deployment of Java stack web applications.
- Build reliable, scalable, and maintainable microservices and AI agents.
- Develop and optimize real-time data processing pipelines using Kafka Streams, Apache Flink, and Spark Streaming for high throughput, reliability, and low-latency performance.
- Collaborate closely with hardware engineering and chip verification teams to understand data and UI/UX requirements and deliver robust, scalable solutions.
- Establish best practices for streaming data architecture, schema management, data retention, and platform observability (monitoring, logging, tracing).
Requirements
- Strong experience with JavaScript/TypeScript and modern frontend frameworks, including building complex data visualization tools and user-facing web applications.
- Expertise designing, building, and debugging distributed Java stack applications, infrastructure, and microservices.
- Deep understanding of Apache Kafka and proven experience building applications with Kafka Streams, Apache Flink, or other event-driven data pipelines.
- Detailed knowledge of distributed systems principles, concurrency, data structures, and algorithms.
- Deep understanding of scalable data caching solutions, specifically Redis.
- Excellent planning, presentation, and communication skills.
- BS degree (or equivalent experience) with 5+ years of relevant experience, or MS degree with 3+ years of relevant experience.
Ways to stand out from the crowd
- Demonstrable knowledge of the Elastic Stack (Elasticsearch, Kibana, Logstash) for logging and analytics.
- Experience with agentic AI frameworks (e.g., LangChain), building LLM-powered autonomous agents, or integrating LLMs with real-time data streams for automated analysis or decision-making.
- Experience working with modern observability using OpenTelemetry (Grafana).
- Background with containerization and orchestration (Docker, Kubernetes).
- Some experience with or understanding of the chip design process and/or EDA verification workflows.
Compensation and benefits
- Base salary range (Level 3): 152,000 USD - 241,500 USD per year.
- Base salary range (Level 4): 184,000 USD - 287,500 USD per year.
- Eligibility for equity and benefits (see provided NVIDIA links in the original posting).
Additional information
- Location: Santa Clara, California, United States. #LI-Hybrid
- Applications accepted at least until June 28, 2026.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer committed to inclusive hiring practices.