Senior Full-Stack Software Engineer – Verification Data Platform
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.
ElasticSearch @ 7
Grafana @ 4
Kafka @ 4
Linux @ 3
Redis @ 7
Kibana @ 7
TypeScript @ 4
Python @ 4
Spark @ 4
Java @ 4
Algorithms @ 4
Data Structures @ 4
Distributed Systems @ 4
Flink @ 4
Spark Streaming @ 4
Communication @ 4
JavaScript @ 4
Vue.js @ 4
Microservices @ 4
Debugging @ 4
LLM @ 4
OLAP @ 4
OpenTelemetry @ 4
GPU @ 4
Observability @ 4
AI @ 4
Data Visualization @ 4
Agentic AI @ 4
ClickHouse @ 4
Data Pipelines @ 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. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing, where GPUs power computers, robots, and self-driving cars that can understand the world.
We are looking for a Senior Full-stack web applications software architect to join our Hardware Infrastructure team. The team is building the next-generation event-driven data platform to power NVIDIA's GPU development efforts. The platform delivers high-availability infrastructure for real-time data processing, streaming analytics, and scalable data-driven applications used across hardware engineering teams for real-time tracking, AI agents development, anomaly detection, and debugging of complex hardware verification and data processing flows.
Responsibilities
- Participate in the full life-cycle of tool development, test, and deployment of web applications and services for test automation and chip verification.
- Develop and optimize real-time data processing pipelines using Kafka Streams, Apache Flink and Spark Streaming, ensuring high throughput, reliability, and low-latency performance.
- Collaborate closely with hardware engineering and chip verification teams to understand data requirements and deliver robust, scalable data solutions and UIs.
- Establish optimal guidelines for streaming data architecture, schema management, data retention and platform observability (monitoring, logging, tracing).
- Build microservices and AI agents that are reliable, scalable, and maintainable.
Requirements
- Proven in-depth knowledge of Java and Python.
- Knowledge of JavaScript/TypeScript and front-end frameworks (e.g., Ember.js, Vue.js) for building data visualization tools.
- Expertise in designing and building distributed systems 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.
- Familiarity with Linux ecosystems (including development and debugging tools).
- BS/MS in Computer Science or related field (or equivalent experience), with 8+ years of experience for BS holders or 5+ years for MS holders.
Ways to stand out
- Deep knowledge of the Elastic Stack (Elasticsearch, Kibana, Logstash) for logging and analytics.
- Experience working with modern observability using OpenTelemetry (Grafana).
- Experience with building agentic AI frameworks, LLM-powered autonomous agents, or integrating LLMs with real-time data streams for automated analysis or decision-making.
- Familiarity with chip design process and/or EDA verification workflows.
- Working experience with modern OLAP solutions like ClickHouse.
Compensation & Benefits
- Base salary range (Level 4): 184,000 USD - 287,500 USD.
- Base salary range (Level 5): 224,000 USD - 356,500 USD.
- Eligible for equity and benefits.
Applications for this job will be accepted at least until March 16, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.