Staff Cloud and AI Solutions Architect

General Motors

. Define and evolve the target architecture for scalable mapping data foundations, including data models, storage patterns, ingestion and transformation pipelines, APIs, data access, metadata, lineage, quality controls, and governance .

Posted 9/18/2026full-timeWarren • California • United StatesLead💰 $189,300 - $290,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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

Demonstrates expertise in defining scalable architecture for mapping data foundations, implementing cloud-native solutions, and applying AI to enhance data discovery and analysis. Strong leadership in technical direction, mentoring, and cross-team collaboration is essential.

Highest-signal resume keywords

Cloud-Native SolutionsData EngineeringAI Application DevelopmentInfrastructure As CodeTechnical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonGoJavaC++Data ModelingData TransformationAPIsCI/CDObservabilityReliability Engineering

Soft Skills

Strong Communication SkillsMentoringInfluencing Technical Direction

Tools & Technologies

AzureAWSGoogle Cloud PlatformKubernetesTerraformDatabricksSparkKafkaEvent-Streaming TechnologiesVector Databases

Industry Keywords

AutomotiveSoftware-Defined VehiclesADASAutonomous DrivingMappingGeospatial SystemsRoboticsSimulationSafety-Sensitive DomainsHigh-Volume Data Consumers

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformJavaKafkaKubernetesPySparkPythonSparkTerraformC++Go

About the role

Key responsibilities & impact

Define and evolve the target architecture for scalable mapping data foundations, including data models, storage patterns, ingestion and transformation pipelines, APIs, data access, metadata, lineage, quality controls, and governance
Build, productionize, and scale reusable cloud-native solutions and services for mapping databases
Establish data contracts, validation frameworks, observability, and operational standards for trustworthy mapping data
Design and implement cloud-first solutions using infrastructure as code, automated deployment, containerized services, CI/CD, monitoring, and production-readiness practices
Partner with map creation, map delivery, validation, simulation, embedded software, data science, and platform teams
Identify opportunities to apply AI to data discovery, technical search, map-data analysis, validation, diagnostics, release readiness, incident triage, and engineering productivity
Design and productionize knowledge-grounded Agentic AI solutions using approved documentation, code, metadata, telemetry, and operational knowledge
Define architecture and operating models for smart agents, including retrieval, tool use, orchestration, access controls, evaluation, observability, human oversight, and safe deployment
Create scalable cloud patterns for AI agents and data services across environments and teams
Build reference implementations and reusable frameworks for cloud, data, and AI adoption
Lead architecture discussions, design reviews, and technical workshops; clarify ownership and resolve cross-team technical seams
Mentor engineers through technical guidance, design feedback, code reviews, and engineering examples
Balance near-term delivery with maintainability, simplification, security, reliability, and responsible AI use

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering, Data Engineering, Artificial Intelligence, or a related technical field; equivalent practical experience may be considered
10+ years of professional software engineering experience building and operating production systems
Senior technical leadership across architecture, design, implementation, and production operations
Strong experience with cloud-native and distributed systems, scalable services, asynchronous or event-driven workflows, data-intensive applications, and reliability engineering
Hands-on experience with Azure, AWS, or Google Cloud Platform
Experience with infrastructure as code, containers or Kubernetes, CI/CD, automated testing, observability, cloud security, and production operations
Strong programming experience in Python, Go, Java, C++, or a comparable production language
Experience designing data platforms, data services, or large-scale data pipelines, including data modeling, storage, transformation, APIs, data quality, and governance
Experience applying AI, machine learning, generative AI, retrieval-augmented generation, or workflow automation to practical software engineering or business problems
Understanding of Agentic AI or multi-step workflow patterns, including tool integration, retrieval, orchestration, evaluation, monitoring, and access control
Ability to influence technical direction across teams without formal organizational authority
Strong written and verbal communication skills
Preferred: experience in automotive, software-defined vehicles, ADAS, autonomous driving, mapping, geospatial systems, robotics, simulation, or other safety- and scale-sensitive domains
Preferred: experience with Azure, Databricks, Terraform, Kubernetes, Spark or PySpark, Kafka or other event-streaming technologies, and modern data-lake or lakehouse architectures
Preferred: experience with vector databases, semantic search, knowledge graphs, metadata platforms, document intelligence, or knowledge-grounded AI applications
Preferred: experience designing and operating internal developer platforms, engineering productivity tools, or self-service cloud capabilities
Preferred: experience with model-training, simulation, offline analytics, digital-twin, or other high-volume data consumers
Preferred: experience defining AI quality, security, privacy, governance, and responsible-use practices for internal engineering tools
Preferred: experience scaling reusable engineering capabilities across multiple teams and managing tradeoffs among delivery speed, performance, reliability, and cost

Benefits

Comp & perks

Bonus potential through an incentive pay program based on company performance, job level, and individual performance
Medical insurance
Dental insurance
Vision insurance
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation and holidays
Tuition assistance programs
Employee assistance program
GM vehicle discounts
Role-related assessment and/or pre-employment screening where applicable
Reasonable accommodations for job seekers with disabilities