Senior Full-stack Software Engineer – Verification Data and Visualization Platform

Posted Yesterday
Be an Early Applicant
3 Locations
In-Office
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design, build, and modernize full‑stack web applications and microservices for a real‑time event-driven data and visualization platform. Develop and optimize streaming data pipelines (Kafka, Flink, Spark), integrate observability, caching (Redis), and AI agents, and collaborate with hardware verification teams for scalable, low-latency solutions.
Summary Generated by Built In

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, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are now looking for a Senior Full-stack web applications software architect to join our Hardware Infrastructure team! Our team is building the next-generation event-driven data and visualization platform to power NVIDIA's GPU development efforts. We deliver the high-availability infrastructure that powers real-time data processing, streaming analytics, and scalable data-driven applications. This platform is essential for hardware engineers and management across the company, producing the core services used for real-time tracking, AI agents development, anomaly detection, and debugging of complex hardware verification and data processing flows.

What you’ll be doing:

  • Front end application modernization 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, test, and deployment of Java stack web applications.

  • Build microservices and AI agents that are reliable, scalable, and maintainable.

  • 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 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).

What we need to see:

  • Strong experience with JavaScript/TypeScript and modern frontend frameworks--building complex data visualization tools and user-facing web applications.

  • Expertise in 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 the scalable data caching solution, specifically Redis.

  • Excellent planning, presentation, and communication skills.

  • BS degree (or equivalent experience) with 5+ years of relevant experience, 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.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/ 
#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 28, 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

  • Strong experience with JavaScript/TypeScript and modern frontend frameworks
  • Expertise in 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 relevant experience, or MS degree with 3+ years relevant experience
  • Experience with the Elastic Stack (Elasticsearch, Kibana, Logstash) for logging and analytics
  • Experience with agentic AI frameworks (e.g., LangChain) or integrating LLMs with real-time data streams
  • Experience with OpenTelemetry and modern observability (Grafana)
  • Background with containerization and orchestration (Docker, Kubernetes)
  • Some experience with or understanding of the chip design process and/or EDA verification workflows

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.

NVIDIA Insights

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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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