System Software Engineer, Engineering Workflow Platform

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

System Software Engineer to build and maintain production workflow infrastructure for large-scale chip engineering, evolving existing Tcl, Make, Perl, Python, YAML, and job-launch infrastructure into a control-plane platform. Requires strong Linux, automation, configuration systems, scripting, and production infrastructure fundamentals.

What you'd actually do

  1. Build and maintain workflow-platform features across YAML configuration, generated artifacts, Make targets, Perl/Python utilities, Tcl checks, and structured output files
  2. Help model workflow stages, inputs, outputs, validation signals, generated files, dependencies, status, and ownership in configuration and manifests
  3. Create machine-readable check results, run manifests, provenance records, log summaries, and status outputs that make behavior easier to inspect and debug
  4. Strengthen early-failure checks for missing files, stale generated data, invalid configuration, bad environment setup, scheduler issues, and incomplete run state
  5. Add and test integrations with distributed job execution, shared compute, filesystem state, data-fidelity tracking, and dependency tracing

Skills

Required

  • Linux
  • automation
  • configuration systems
  • scripting
  • production infrastructure
  • Python
  • Perl
  • Go
  • C++
  • Make
  • YAML
  • JSON
  • shell scripting
  • debugging
  • written communication

Nice to have

  • chip-design
  • CAD-flow
  • semiconductor design
  • EDA workflows
  • RTL
  • synthesis
  • place-and-route
  • timing
  • signoff
  • ECO
  • handoff flows
  • workflow engines
  • build systems
  • CI/CD platforms
  • job schedulers
  • deployment automation
  • data pipelines
  • large-scale engineering automation
  • Tcl
  • structured logs
  • validation frameworks
  • provenance tracking
  • dashboards
  • observability tools
  • shared filesystems
  • partial writes
  • stale state
  • locking
  • reproducibility
  • generated artifacts
  • batch jobs
  • migrations
  • documentation
  • debug tooling

What the JD emphasized

  • Strong Linux fundamentals
  • Practical programming experience in Python, Perl, Go, C++
  • 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