Principal Software Engineer - Vehicle AI

GM • Mountain View, CA

1d • Hybrid

About The Position

General Motors is building the future of intelligent in-cabin experiences, and we are looking for a Principal Software Engineer to serve as a technical leader and authority for our next-generation In-Vehicle AI Assistant platform. Focused on cabin intelligence, voice interaction, and conversational AI, this role bridges the entire edge-to-cloud spectrum—spanning the Android Automotive OS (AAOS) client application layer, cloud AI orchestration pipelines, and backend service integration. In this high-impact role based out of our Mountain View, CA or Seattle, WA offices, you will shape the multi-year technical vision for our in-cabin assistant platform. You will work extensively across cross-functional boundaries—aligning Cloud AI/ML, In-Cabin UX, Vehicle Platform, Security, and Infrastructure teams to build a cohesive, scalable ecosystem. If you excel at driving technical strategy across complex distributed systems and bringing clarity to large-scale engineering initiatives, this role offers an unmatched opportunity to define the assistant experience for millions of vehicles worldwide.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, or equivalent practical experience.
• 12+ years of professional software development experience, with a proven track record of designing large-scale distributed systems spanning client applications and cloud microservices.
• Broad technical depth across client-side Android architecture (Kotlin/Java) and backend cloud integration (microservices, REST, gRPC, streaming APIs).
• Demonstrated history of cross-functional (XFN) technical leadership, driving architectural alignment and consensus across multiple engineering organizations.
• Deep expertise in client-server interaction patterns, state synchronization, and low-latency network communication protocols.
• Proven ability to define multi-year technical roadmaps and translate high-level product vision into concrete, scalable platform architectures.

Nice To Haves

• Master’s or Ph.D. in Computer Science, Electrical Engineering, or a related field.
• Technical domain expertise in conversational AI architectures, voice assistant frameworks, or agentic LLM orchestration layers.
• Familiarity with Android Automotive OS (AAOS) applications or in-cabin system constraints.
• Background in edge-cloud hybrid computing, including client-side machine learning execution and server-side model streaming.
• Exceptional technical communication skills, with a track record of articulating complex architectural trade-offs to senior leadership and non-technical stakeholders.

Responsibilities

• Define and own the end-to-end architecture for GM’s In-Vehicle AI Assistant platform across both the Android client application layer and cloud backend integration services.
• Drive cross-functional technical strategy, collaborating with Cloud AI/ML, In-Cabin UX, Product Management, Security, and Data Engineering teams to align system boundaries and interface contracts.
• Architect the hybrid edge-cloud orchestration layer, optimizing trade-offs between on-device latency, network bandwidth, cloud compute cost, and offline reliability.
• Establish engineering standards and API protocols for high-performance, real-time client-server communication using gRPC and streaming audio/text interfaces.
• Evaluate and integrate emerging Artificial Intelligence / Machine Learning (AI/ML) agent frameworks, large language model orchestrators, and tool execution engines into the in-cabin assistant ecosystem.
• Unblock critical architectural dependencies across multiple engineering pods, resolving complex trade-offs in system reliability, privacy, and data streaming.
• Drive platform-wide testing, evaluation pipelines, and telemetry standards to measure end-to-end voice latency, response accuracy, and system health.
• Mentor and grow Staff and Senior engineers across client and backend disciplines, fostering a culture of technical rigor and architectural excellence.

Benefits

• Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.
• Company Vehicle : Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate.
• This Job may be eligible for relocation benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal