Principal Software Engineer – Vehicle AI

General Motors

Principal Software Engineer architecting General Motors’ in-vehicle conversational AI platform across Android Automotive and cloud services. Leading edge-cloud orchestration, real-time APIs, and cross-functional engineering strategy.

Posted 9/9/2026full-timeMountain View • California, Texas, Washington • 🇺🇸 United StatesLead💰 $238,700 - $365,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in defining and owning end-to-end architecture for In-Vehicle AI Assistant platforms, with a strong focus on Android client applications and cloud backend integration. Proven ability to lead cross-functional teams and establish engineering standards for real-time communication and AI/ML integration.

Highest-signal resume keywords

End-To-End Architecture DesignAndroid Architecture Using Kotlin/JavaCloud Integration and MicroservicesCross-Functional Technical LeadershipAI/ML Framework Integration

ATS Keywords

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Hard Skills

Software DevelopmentDistributed Systems DesignClient-Server Interaction PatternsLow-Latency Network CommunicationAPI Protocols (gRPC, REST)Real-Time Communication StandardsVoice Latency MeasurementSystem Health EvaluationHybrid Edge-Cloud OrchestrationTechnical Roadmap Definition

Soft Skills

Technical CommunicationMentoring

Tools & Technologies

Android Automotive OSAI/ML Agent FrameworksStreaming APIsTelemetry Standards

Certifications & Qualifications

Bachelor’s Degree in Computer ScienceMaster’s or Ph.D. in Computer Science or Related Field

Industry Keywords

In-Vehicle AI AssistantConversational AI ArchitecturesVoice Assistant FrameworksEdge-Cloud Hybrid Computing

Tech Stack

Tools & technologies

AndroidCloudDistributed SystemsGRPCJavaKotlinMicroservices

About the role

Key responsibilities & impact

Define and own end-to-end architecture for GM’s In-Vehicle AI Assistant platform across Android client applications and cloud backend integration services
Drive cross-functional technical strategy with Cloud AI/ML, In-Cabin UX, Product Management, Security, and Data Engineering teams
Architect hybrid edge-cloud orchestration, balancing on-device latency, network bandwidth, cloud compute cost, and offline reliability
Establish engineering standards and API protocols for real-time client-server communication using gRPC and streaming audio/text interfaces
Evaluate and integrate AI/ML agent frameworks, large language model orchestrators, and tool execution engines
Resolve architectural dependencies and trade-offs involving reliability, privacy, and data streaming
Drive platform-wide testing, evaluation pipelines, and telemetry standards
Measure voice latency, response accuracy, and system health
Mentor Staff and Senior engineers across client and backend disciplines
Shape the multi-year technical vision for GM’s in-cabin assistant platform

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Computer Engineering, or equivalent practical experience
12+ years of professional software development experience
Proven experience designing large-scale distributed systems spanning client applications and cloud microservices
Technical depth in Android architecture using Kotlin/Java
Experience with backend cloud integration, microservices, REST, gRPC, and streaming APIs
Cross-functional technical leadership across multiple engineering organizations
Expertise in client-server interaction patterns, state synchronization, and low-latency network communication protocols
Ability to define multi-year technical roadmaps and translate product vision into scalable platform architectures
Preferred: Master’s or Ph.D. in Computer Science, Electrical Engineering, or a related field
Preferred: Expertise in conversational AI architectures, voice assistant frameworks, or agentic LLM orchestration layers
Preferred: Familiarity with Android Automotive OS applications or in-cabin system constraints
Preferred: Background in edge-cloud hybrid computing, client-side machine learning execution, and server-side model streaming
Preferred: Exceptional technical communication skills

Benefits

Comp & perks

Bonus potential through an incentive pay program based on company performance, job level, and individual performance
Company vehicle evaluation program, including assignment of a General Motors vehicle, subject to motor vehicle report review
Potential relocation benefits
Benefits supporting well-being at work and home
Reasonable accommodations for applicants with disabilities