Senior Platform Engineer, Design Automation

NVIDIA•Us, CA

About The Position

NVIDIA is seeking a Senior Platform Engineer, Design Automation to join a team responsible for the software platform used by chip-design teams. This platform supports launching, monitoring, debugging, and improving large-scale semiconductor design workflows. The systems handle hundreds of thousands of design jobs daily, supporting over 1,000 designers across various product lines. This role involves distributed systems, developer tooling, workflow orchestration, data infrastructure, and semiconductor design methodology. The engineer will modernize production services, enhance design-flow infrastructure reliability and usability, and leverage design execution data for actionable insights.

Requirements

Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
12+ years of software engineering experience, including the design and operation of distributed production systems.
Strong Python and JavaScript/TypeScript development skills, with experience building backend services, APIs, and modern web applications.
Hands-on experience building applied-AI solutions using LLMs, RAG, agents, or related technologies.
Strong understanding of system design, databases, reliability, observability, CI/CD, and Linux operations.
Strong technical communication and multi-functional leadership skills.

Nice To Haves

Experience with EDA, VLSI, physical design, static timing analysis, or RTL-to-GDS workflows.
Background with Temporal, Airflow, Argo, Jenkins, or similar orchestration platforms.
Experience with Docker, Kubernetes, HPC schedulers, or large compute farms.
Background with SQL/NoSQL databases, Kafka, Elasticsearch, Grafana, or similar platforms.

Responsibilities

Architect, build and operate AI-enabled platforms for large-scale VLSI workflows.
Develop reliable backend services, APIs, data models, event-driven systems, and workflow orchestration.
Create intuitive web applications for launching, monitoring, debugging, and analyzing design jobs.
Apply LLMs, RAG, agents, and automation to accelerate debugging, recommendations, and operational support.
Build telemetry, analytics, and dashboards for workflow health, performance, and quality of results.
Collaborate with EDA, design methodology, and infrastructure teams to improve productivity and tapeout reliability.