Qualcomm
Principal Software Engineer, AI Software Automotive Lead
$224K–$335K
San Diego, California · On-site · Principal · Full-time · Posted Sep 17, 2026
- Experience
- 8+ years with a bachelor’s degree, 7+ years with a master’s degree, or 6+ years with a PhD; preferred qualifications state 15+ years of industry experience.
- Education
- Bachelor’s, master’s, or PhD in Computer Science, Engineering, Information Systems, or a related field.
About the job
Leads the design, integration, and deployment of AI software for Qualcomm automotive platforms, serving as the technical interface among customers, the Automotive Business Unit, and engineering teams.
What you'll do
- Represent AI Software in customer engagements and translate automotive requirements into architectures, roadmaps, and execution plans.
- Lead cross-functional development and delivery of AI software features, including optimization of Qualcomm’s AI Stack for automotive use cases.
- Guide platform architecture, production deployment, and resolution of performance, reliability, safety, and quality issues; mentor engineers.
What they ask for
- Bachelor’s degree in a related field and 8+ years of relevant work experience; or master’s degree and 7+ years; or PhD and 6+ years.
- Preferred qualifications include expert-level C/C++ proficiency and experience leading large technical initiatives across teams.
- Preferred qualifications include customer-facing technical leadership and experience with automotive software platforms or production programs.
- Preferred qualifications include experience with AI/ML frameworks, model deployment and optimization, and edge AI inference.
Nice to have
- Experience with automotive safety and quality standards such as ISO 26262, ASPICE, and ISO/SAE 21434.
- Experience with Qualcomm AI technologies, AI-native and agentic software development, Python, and globally distributed teams.
Pay
$223,600.00 - $335,400.00 (base salary)
Tools
C/C++, QNX, Android Automotive, Linux, AUTOSAR, PyTorch, TensorFlow, ONNX
AI focus
Develops and deploys automotive AI software across computer vision, perception, driver monitoring, voice assistants, LLMs, multimodal AI, and generative AI; includes model preparation, optimization, runtime, and edge inference acceleration.
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