Senior Software Engineer, Infrastructure and Tooling - DriveOS
NVIDIA · Remote · Santa Clara, United States · 1d ago
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. Our Infrastructure and Tooling team makes the engineering environment behind that platform coherent, practical, and scalable — and we’re looking for a Senior Software Engineer to help shape it.
This role combines software engineering and AI-enabled automation with first-principles thinking: building tools that help teams deliver reliable software and evidence that is fit for product risk. You will help a globally distributed organization turn quality, safety, and cybersecurity expectations into integrated engineering workflows — embedding intelligent agents, automated reasoning, and data-driven insights where they improve development efficiency and product quality.
What you’ll be doing:
- 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 tasks such as requirements analysis, test generation, defect triage, and safety documentation.
- Translate multi-functional collaborator requirements into process-automation solutions that operate in environments aligned with automotive standards (ISO 26262, ISO 21434) and quality models (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.
What we need to see:
- BS or MS in Computer Science, or equivalent experience, with 8+ years 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 (GitLab CI, Jenkins, or similar) and infrastructure-as-code tools (Terraform, Ansible).
- Experience building production-grade, full-stack systems — backend microservices (Python, Node.js, Go), RESTful and GraphQL APIs, relational and NoSQL datastores, graph databases (e.g., Neo4j), and modern web interfaces (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 UIs for agent interaction.
- Strong SQL and data-warehousing skills for managing high-volume metrics across multiple programs.
- Clear communication and collaborative problem-solving skills.
Ways to stand out from the crowd:
- 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 (VS Code extensions, IDE plugins, 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.
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.