NVIDIA
Principal Process Architect, Automotive Software
$272K–$431K
US, CA, Santa Clara +5 · Principal · Full-time · Posted Aug 18, 2026
- Location
- US, CA, Santa Clara
US, TX, Remote
US, NY, Remote
US, WA, Remote
US, CA, Remote
US, MI, Remote - Experience
- 15+ years in automotive or other safety-critical product development, including process architecture, engineering quality, systems engineering, or technical program leadership.
- Education
- Bachelor’s degree or equivalent experience in engineering, computer science, systems engineering, quality, or a related field.
About the job
Leads the architecture and governance of DriveOS development processes, aligning quality, safety, cybersecurity, and AI/ML safety practices across teams and product variants.
What you'll do
- Define and govern DriveOS processes, roles, interfaces, and risk-based tailoring.
- Set maturity, release-readiness, and quality-gate criteria; align plans, evidence, dependencies, and handoffs.
- Improve workflows and training using lessons from defects and assessments, including automation and AI-assisted workflows where they reduce risk, rework, or cycle time.
What they ask for
- Bachelor’s degree or equivalent experience in engineering, computer science, systems engineering, quality, or a related field.
- Deep understanding of Automotive SPICE and the software and systems development lifecycle.
- Hands-on experience with automotive functional safety, cybersecurity, and AI/ML safety requirements, including ISO 26262, ISO/SAE 21434, and ISO 8800.
- Track record building risk-based tailoring and quality gates in complex, multi-variant product environments.
Nice to have
- Success implementing or modernizing an automotive quality-management system or development process across multiple teams or product variants.
- Experience with HW SPICE, relevant standards bodies or working groups, or safety- or security-critical process tooling.
Pay
272,000 USD - 431,250 USD (base salary)
Tools
Automotive SPICE, ISO 26262, ISO/SAE 21434, ISO 8800, HW SPICE
AI focus
Drive process automation and AI-assisted workflows that demonstrably reduce risk, rework, or cycle time while preserving governance, traceability, and engineering judgment; the posting also mentions AI/ML safety requirements.
Model-written summary · the original posting is authoritative