System Software Engineer, Engineering Workflow Platform

NVIDIA•Santa Clara, CA

4d•$152,000 - $287,500

About The Position

NVIDIA is building the next generation of production workflow infrastructure for large-scale chip engineering. This platform turns intent, layered configuration, generated files, tool execution, distributed jobs, validation checks, and shared project state into observable, repeatable workflows. This role is for a systems-minded engineer who may not have prior chip-design or CAD-flow experience, but has strong fundamentals in Linux, automation, configuration systems, scripting, and production infrastructure. You will work alongside senior platform and flow architects to evolve existing Tcl, Make, Perl, Python, YAML, and job-launch infrastructure into a clearer control-plane platform for complex engineering workflows.

Requirements

B.S. or M.S. in CS, EE, CE, or equivalent experience
4+ years building automation, developer infrastructure, workflow platforms, distributed systems, test infrastructure, or engineering productivity tools
Strong Linux fundamentals, including shell debugging, environment setup, filesystem behavior, process execution, logs, exit codes, and background jobs
Practical programming experience in Python, Perl, Go, C++, or similar, and comfortable reading and modifying Make, YAML, JSON, and shell-based infrastructure
Ability to reason carefully about configuration layers, generated files, schemas, validation rules, compatibility, and incremental migration of legacy systems
Strong debugging habits, clear written communication, and experience improving production infrastructure without destabilizing active users

Nice To Haves

Exposure to semiconductor design or EDA workflows, especially RTL, synthesis, place-and-route, timing, signoff, ECO, or handoff flows
Background with workflow engines, build systems, CI/CD platforms, job schedulers, deployment automation, data pipelines, 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
Background with shared filesystems, partial writes, stale state, locking, reproducibility, generated artifacts, batch jobs, tests, migrations, documentation, or debug tooling

Responsibilities

Build and maintain workflow-platform features across YAML configuration, generated artifacts, Make targets, Perl/Python utilities, Tcl checks, and structured output files
Help 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 that make behavior easier to inspect and debug
Strengthen early-failure checks for missing files, stale generated data, invalid configuration, bad 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