Senior Software Engineer, Infrastructure and Tooling

This is a fully remote position, open to applicants in California.

📋 Description

• Design and develop highly available automation systems, developer tools, and intelligent dashboards to enhance and monitor the quality of DriveOS builds and releases.

• Collaborate across the organization to influence infrastructure roadmaps and unify tooling initiatives.

• Create AI-native pipelines that incorporate LLM-based agents, RAG systems, and multi-agent orchestration within engineering workflows.

• Automate the analysis of requirements, generation of tests, triaging of defects, and documentation for safety.

• Convert collaborator needs into process-automation solutions that comply with ISO 26262, ISO 21434, and ISO 25010 standards.

• Construct integrated data pipelines that aggregate telemetry from global systems.

• Present executive-level insights through sophisticated visualization and predictive quality metrics.

• Assess and implement emerging AI capabilities, including code-generation copilots, agentic coding assistants, and automated documentation tools.

• Establish and implement governance policies for AI-assisted tooling outputs to guarantee traceability, auditability, and compliance.

• Enhance tooling quality and architectural standards.

• Mentor and assist engineers at all levels.

⛳️ Requirements

• Bachelor’s or Master’s degree in Computer Science, or equivalent experience.

• Over 8 years of experience in infrastructure, DevOps, or software tooling.

• Strong expertise in Python programming.

• Knowledge of tooling architecture and design patterns.

• Experience in managing enterprise-scale CI/CD environments (such as GitLab CI, Jenkins, or similar systems).

• Familiarity with infrastructure-as-code tools (e.g., Terraform, Ansible).

• Experience in building production-grade, full-stack systems, including Python, Node.js, Go, RESTful and GraphQL APIs, as well as relational and NoSQL databases, graph databases like Neo4j, and frameworks like React, Next.js, or TypeScript.

• Practical experience in deploying LLM and agentic applications, which includes agent frameworks, tool integration, MCP-based systems, memory and orchestration, prompt engineering, guardrails, evaluation, and RAG/GraphRAG architectures.

• Experience in developing internal developer portals and AI-powered interfaces, including chat-based or conversational UIs.

• Strong SQL and data warehousing capabilities.

• Excellent communication and collaborative problem-solving abilities.

• Experience in developing and deploying tools within distributed organizations.

• Previous experience in the automotive, aerospace, or medical sectors with stringent regulatory and safety certifications.

• Experience in creating plugin-based or extensible tooling platforms, such as VS Code extensions, IDE plugins, or CLI toolchains.

• Experience in building and maintaining AI evaluation harnesses, including automated regression testing for LLM outputs, prompt versioning, and safety-critical guardrails for AI-generated artifacts.

🏝️ Benefits

• Equity

• Benefits