Principal Software Engineer – Vehicle AI

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California (MO)

On-site

USD 200,000 - 260,000

Full time

3 days ago

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Job summary

General Motors seeks a Senior Architect to define and own the end-to-end In-Vehicle AI Assistant platform. You will shape architecture for Android clients and cloud services, guiding cross-functional teams across UX, security, and data engineering to ensure seamless real-time communication and AI/ML integration.

You will lead multi-year technical roadmaps, evaluate AI/LLM orchestration layers, and drive reliability, latency, and privacy across hybrid edge-cloud environments.

Qualifications

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 ML execution, and server-side model streaming.
Preferred: Exceptional technical communication skills.

Responsibilities

Define and own end-to-end architecture for In-Vehicle AI Assistant platforms 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, and offline reliability.
Establish engineering standards and API protocols for real-time client-server communication using gRPC and streaming interfaces.
Evaluate and integrate AI/ML agent frameworks, large language model orchestrators, and tool execution engines.

Skills

End-to-End Architecture

Android Architecture

Cloud Integration

Cross-Functional Leadership

AI/ML Frameworks

Education

Bachelor's Degree in CS/CE

Master/PhD in CS/EE (preferred)

Tools

Android Automotive OS

Streaming APIs

Telemetry Standards

gRPC

REST

Job description

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

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

Core Competencies

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.

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