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System Software Engineer, Engineering Workflow Platform

NVIDIA
August 22, 2026
Full-time
On-site
Santa Clara, California, United States
$152,000 - $287,500 USD yearly
EDA Jobs, Level - Mid-Career

Job Title

System Software Engineer, Engineering Workflow Platform

Role Summary

Develop and maintain the production workflow platform that coordinates configuration, generated artifacts, tool execution, distributed jobs, validation checks, and project state for large-scale chip engineering.

You will work with platform and flow architects to convert legacy Make/Perl/Tcl-based infrastructure into a clearer control-plane for complex engineering workflows.

Experience Level

Mid-level β€” typically 4+ years building automation, developer infrastructure, workflow platforms, distributed systems, test infrastructure, or engineering productivity tools.

Responsibilities

Primary day-to-day responsibilities include evolving workflow control plane features, improving diagnostics, and integrating distributed execution systems.

  • Build and maintain workflow-platform features across YAML configuration, generated artifacts, Make targets, Perl/Python utilities, Tcl checks, and structured output files.
  • Model workflow stages, inputs/outputs, validation signals, generated files, dependencies, status, and ownership in configuration and manifests.
  • Create machine-readable check results, run manifests, provenance records, log summaries, and status outputs for observability and debugging.
  • Improve early-failure checks for missing files, stale generated data, invalid configuration, environment setup, scheduler issues, and incomplete run state.
  • Add and test integrations with distributed job execution, shared compute, filesystem state, data-fidelity tracking, and dependency tracing.
  • Work with senior engineers and users to reproduce failures, trace configuration behavior, improve diagnostics, update documentation, and preserve existing workflows.

Requirements

Must-have technical skills and experience required to perform the role.

  • 4+ years working on automation, developer infrastructure, workflow platforms, distributed systems, test infrastructure, or engineering productivity tools.
  • Strong Linux fundamentals: shell debugging, environment setup, filesystem behavior, process execution, logs, exit codes, background jobs.
  • Practical programming experience in Python, Perl, Go, C++, or similar; ability to read and modify Make, YAML, JSON, and shell-based infrastructure.
  • Ability to reason about configuration layers, generated files, schemas, validation rules, compatibility, and incremental migration of legacy systems.
  • Strong debugging habits and clear written communication; experience improving production infrastructure without destabilizing active users.

Nice-to-have (helps but not required):

  • Exposure to semiconductor design or EDA workflows (RTL, synthesis, place-and-route, timing, signoff, ECO, handoff flows).
  • Background with workflow engines, build systems, CI/CD platforms, job schedulers, deployment automation, or large-scale engineering automation.
  • Experience improving legacy Make, Perl, shell, Python, or Tcl systems while preserving existing behavior.
  • Experience creating structured logs, JSON/YAML schemas, validation frameworks, provenance tracking, dashboards, or observability tools.
  • Familiarity with shared filesystems, partial writes, stale state, locking, reproducibility, generated artifacts, batch jobs, migrations, documentation, or debug tooling.

Education Requirements

B.S. or M.S. in Computer Science, Electrical Engineering, Computer Engineering, or a closely related technical field β€” or equivalent practical experience.


About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.

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Date Posted: 2026-08-21