Senior Software Engineer, Infrastructure and Tooling

NVIDIA

. Design and implement highly available automation systems, developer tooling, and intelligent dashboards to improve and monitor DriveOS build and release quality .

Posted 10/5/2026full-timeRemote • California • United StatesSenior💰 $184,000 - $356,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing automation systems and developer tooling, with a strong focus on AI-native pipelines and compliance with ISO standards. Proficient in managing CI/CD environments and building production-grade systems across various technologies.

Highest-signal resume keywords

Python ProficiencyCI/CD Environment ManagementInfrastructure-As-Code ToolsAI-Native Pipeline ArchitectureAutomotive Industry Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonNode.jsGoRESTful APIsGraphQL APIsSQLTerraformAnsibleNeo4jData Warehousing

Soft Skills

Clear CommunicationCollaborative Problem-Solving

Tools & Technologies

GitLab CIJenkinsVS Code ExtensionsIDE PluginsCLI Toolchains

Certifications & Qualifications

BS or MS in Computer ScienceISO 26262 ComplianceISO 21434 ComplianceISO 25010 Compliance

Industry Keywords

AutomotiveAerospaceMedicalRegulatory ComplianceSafety Certifications

Tech Stack

Tools & technologies

AnsibleGraphQLJavaScriptJenkinsNeo4jNext.jsNode.jsNoSQLPythonReactSQLTerraformTypeScriptGo

About the role

Key responsibilities & impact

Design and implement highly available automation systems, developer tooling, and intelligent dashboards to improve and monitor DriveOS build and release quality
Partner across the organization to shape infrastructure roadmaps and consolidate tooling initiatives
Architect AI-native pipelines integrating LLM-based agents, RAG systems, and multi-agent orchestration into engineering workflows
Automate requirements analysis, test generation, defect triage, and safety documentation
Translate collaborator requirements into process-automation solutions aligned with ISO 26262, ISO 21434, and ISO 25010
Build integrated data pipelines aggregating telemetry from global systems
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
Define and deploy governance policies for AI-assisted tooling outputs to ensure traceability, auditability, and compliance
Raise tooling quality and architectural standards
Coach and support engineers at all levels

Requirements

What you’ll need

BS or MS in Computer Science, or equivalent experience
8+ years in infrastructure, DevOps, or software tooling
Strong proficiency in Python
Understanding of tooling architecture and design patterns
Experience managing enterprise-scale CI/CD environments (GitLab CI, Jenkins, or similar)
Experience with infrastructure-as-code tools (Terraform, Ansible)
Experience building production-grade, full-stack systems, including Python, Node.js, Go, RESTful and GraphQL APIs, relational and NoSQL datastores, graph databases such as Neo4j, and 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
Strong SQL and data-warehousing skills
Clear communication and collaborative problem-solving skills
Experience developing and deploying tools across distributed organizations
Prior experience in automotive, aerospace, or medical industries with strict regulatory and safety certifications
Experience building plugin-based or extensible tooling platforms, such as VS Code extensions, IDE plugins, or CLI toolchains
Experience building and maintaining AI evaluation harnesses, including automated regression testing for LLM outputs, prompt versioning, and guardrails for safety-critical AI-generated artifacts

Benefits

Comp & perks

Equity
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