Senior Software Engineer, Infrastructure and Tooling - DriveOS

Details

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 safety-critical applications. The Infrastructure and Tooling team makes the engineering environment behind that platform coherent, practical, and scalable.

This role combines software engineering and AI-enabled automation with first-principles thinking. You will build tools that help teams deliver reliable software and evidence fit for product risk. You will also help a globally distributed organization turn quality, safety, and cybersecurity expectations into integrated engineering workflows by embedding intelligent agents, automated reasoning, and data-driven insights where they improve development efficiency and product quality.

Responsibilities

• Design and implement highly available automation systems, developer tooling, and intelligent dashboards that improve and monitor the quality of DriveOS builds and releases.
• Partner with teams across the organization to shape infrastructure roadmaps and consolidate tooling initiatives.
• Architect AI-native pipelines that integrate LLM-based agents, RAG systems, and multi-agent orchestration into core engineering workflows, automating requirements analysis, test generation, defect triage, and safety documentation.
• Translate multifunctional collaborator requirements into process-automation solutions aligned with automotive standards, including ISO 26262 and ISO 21434, and quality models such as ISO 25010.
• Build integrated data pipelines that aggregate telemetry from global systems and surface executive-level insights through advanced visualization and predictive quality metrics.
• Evaluate and operationalize emerging AI capabilities, including code-generation copilots, agentic coding assistants, and automated documentation tools.
• Help define and deploy governance policies for AI-assisted tooling outputs, ensuring traceability, auditability, and compliance when AI-generated artifacts feed into safety-certified processes.
• Raise the standard for tooling quality and architectural guidelines.
• Coach and support engineers at all levels, fostering a culture of technical growth.

Requirements

• BS or MS in Computer Science, or equivalent experience, with 8+ years of experience in infrastructure, DevOps, or software tooling.
• Strong proficiency in Python and a solid understanding of tooling architecture and design patterns.
• Experience managing enterprise-scale CI/CD environments using GitLab CI, Jenkins, or similar tools, as well as infrastructure-as-code tools such as Terraform and Ansible.
• Experience building production-grade, full-stack systems, including backend microservices with Python, Node.js, or Go; RESTful and GraphQL APIs; relational and NoSQL datastores; graph databases such as Neo4j; and modern web interfaces using React, Next.js, or TypeScript.
• Hands-on experience deploying LLM and agentic applications, including agent frameworks, tool integration, MCP-based systems, memory and orchestration, prompt engineering, guardrails, evaluation, and RAG/GraphRAG architectures.
• Experience building internal developer portals and AI-powered interfaces, including chat-based or conversational user interfaces for agent interaction.
• Strong SQL and data-warehousing skills for managing high-volume metrics across multiple programs.
• Clear communication and collaborative problem-solving skills.

Preferred Qualifications

• Experience developing and deploying tools across distributed organizations.
• Prior experience in automotive, aerospace, or medical industries where process infrastructure must meet strict regulatory and safety certifications.
• Experience building plugin-based or extensible tooling platforms, such as VS Code extensions, IDE plugins, or CLI toolchains, that embed AI capabilities directly into developer workflows.
• Experience building and maintaining AI evaluation harnesses, including automated regression testing for LLM outputs, prompt versioning, and guardrails for safety-critical AI-generated artifacts.

Compensation and Benefits

• Base salary for Level 4: USD 184,000–287,500 per year.
• Base salary for Level 5: USD 224,000–356,500 per year.
• Eligibility for equity and benefits.
• Applications will be accepted at least until October 9, 2026.

NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. NVIDIA uses AI tools in its recruiting processes.