Role at a glance
- Salary
- Not Disclosed
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Education
- Bachelor's
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About the role
Original posting provided by NVIDIA
NVIDIA is harnessing the power of AI and high-performance computing to build the future of mobility. DriveOS is the software platform behind autonomous vehicles and other intelligent machines, combining system software, virtualization, and accelerated computing capabilities for demanding, safety-critical applications. We are seeking a Senior Process Architect to make the system of work behind that platform coherent, practical, and scalable. This role combines automotive process engineering with first-principles judgment: enabling teams to deliver evidence that is fit for product risk, not process for its own sake. You will help a globally distributed organization turn quality, safety, cybersecurity, and AI/ML safety expectations into a coordinated, executable development model.
What You’ll Be Doing:
Lead the canonical DriveOS process architecture, terminology, roles and interfaces across engineering, program management, quality, functional safety, and cybersecurity.
Develop and govern a risk-based tailoring framework that defines variant applicability, decision rights, acceptance criteria, and traceable approvals before execution begins.
Establish process maturity, release-readiness, and quality-gate criteria that surface risk early and support predictable, first-pass acceptance.
Translate internal lifecycle expectations and applicable industry standards into clear, verifiable workflows, templates, guidance, and mentorship for development teams.
Partner with domain leads, program managers, assessors, and tool owners to align plans, evidence, dependencies, and handoffs across product variants.
Convert recurring defects, assessment observations, and release takeaways into durable improvements to the common process, measurements, and training.
Drive process automation and AI-assisted workflows where they demonstrably reduce risk, rework, or cycle time while preserving governance, traceability, and engineering judgment.
Serve as an independent technical authority for process coherence and efficiency, raising gaps with a clear statement of product impact, accountable owner, recovery plan, and date.
What We Need To See:
Bachelor’s degree or equivalent experience in engineering, computer science, systems engineering, quality, or a related field.
15+ years of experience in automotive or other safety-critical product development, including process architecture, engineering quality, systems engineering, or technical program leadership.
Deep understanding of Automotive SPICE, including how process capability, base practices, and generic practices translate into effective engineering behavior and assessable evidence!
Strong understanding of the software and systems development lifecycle, including requirements, architecture, implementation, verification, validation, configuration, change, and release management.
Hands-on experience with automotive functional safety, cybersecurity, and AI/ML safety requirements, including ISO 26262, ISO/SAE 21434, and ISO 8800.
Proven track record to build risk-based tailoring, establish quality gates, and balance compliance needs with program realities in a complex, multi-variant product environment.
Excellent written communication, facilitation, and influence skills; able to make process requirements actionable for engineers and decision-ready for senior leaders.
Experience using data, workflow tooling, and AI-assisted capabilities to improve engineering processes without weakening accountability or traceability.
Ways To Stand Out From The Crowd:
Proven success implementing or modernizing an automotive quality-management system or development process across multiple teams or product variants.
Experience with hardware engineering process models, including HW SPICE, or with the interaction of system, software, and hardware engineering in autonomous-driving programs.
Participation in relevant standards bodies or working groups, such as intacs, VDA QMC, ISO TC22/SC32, or comparable industry forums.
Experience building process tooling, traceability models, measurements, or controlled AI-assisted workflows for safety- or security-critical development.
Credentials or demonstrated proficiency in Automotive SPICE, functional safety, cybersecurity, or AI/ML safety.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.