> Markdown version of [/jobs/ext/4549081-principal-ai-software-engineer-automotive](https://www.wearedevelopers.com/jobs/ext/4549081-principal-ai-software-engineer-automotive). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal AI Software Engineer, Automotive - **Company:** Qualcomm - **Location:** San Diego, CA, United States - **Salary:** $180,000.0 - $260,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, Monitoring of Systems, Machine Learning, Software Architecture, Software Systems, Large Language Models, Automotive Software, Model Inference - **Published:** November 3, 2026 - **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=3046819060-2 ## About the Role * AI software architecture * Machine learning * Model preparation and optimization * AI inference and runtime * Computer vision * Perception systems * Driver monitoring systems * Voice assistants * Large language models * Automotive software integration ## Description Lead the architecture, development, integration, and deployment of AI software for automotive platforms. Serve as a technical interface for automotive customers and internal teams, translating requirements into roadmaps and production-ready solutions across computer vision, driver monitoring, voice AI, and generative AI. Guide cross-functional engineering efforts and mentor engineers., * Lead technical engagement with automotive business units, OEMs, Tier-1 suppliers, and strategic customers. * Represent the organization in customer discussions, architecture reviews, technical deep dives, and issue resolution. * Coordinate design, development, integration, and delivery of AI software features for automotive platforms. * Translate customer and market requirements into technical specifications, architecture proposals, roadmaps, and execution plans. * Improve AI software capabilities across model preparation, optimization, runtime, inference, tooling, and developer workflows. * Guide cross-functional teams, make architecture decisions, mentor engineers, and ensure automotive performance, reliability, security, and safety requirements are met.