Staff Cloud and AI Solutions Architect

Job Description

Production Mapping is looking for a Staff Cloud and AI Solutions Engineer to build and scale future-ready mapping foundations that support the expansion of our mapping databases and the next generation of software-defined vehicle experiences.

This role will combine deep software and cloud engineering with data-platform architecture and practical AI enablement. You will design scalable foundations for mapping data create reusable services and workflows and help transform the teams existing knowledge tools and engineering practices into secure production-ready Agentic AI solutions. Your work will help mapping teams move faster improve data quality and traceability and use cloud-based intelligence in their day-to-day development and operations.

The ideal candidate is a hands-on technical leader who can work across data engineering backend services cloud infrastructure distributed systems developer tooling and AI-enabled workflows. Experience in automotive mapping ADAS SDV robotics or other data-intensive domains is highly desirable.

As a Staff Cloud and AI Solutions Engineer you will provide technical leadership for the solutions services and engineering patterns that make Production Mapping data more scalable trusted discoverable and useful.

You will help define the architecture for a future-ready mapping database ecosystem including data ingestion transformation storage access quality lineage governance and delivery to downstream consumers. You will also identify practical opportunities to apply AI and agentic workflows to engineering work using the knowledge base that already exists across documentation code metadata operational data and team practices.

This is a senior individual-contributor role with broad influence and hands-on delivery responsibility. You will set technical direction build reference implementations establish reusable standards and partner with multiple teams to move solutions from concept to production. Success will come from creating durable capabilities that teams adoptnot from becoming the owner of every mapping system or every AI initiative.

• 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 that support the growth availability performance security and cost efficiency of mapping databases.

• Establish data contracts validation frameworks observability and operational standards that make mapping data trustworthy and easier to consume across engineering teams.

• 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 to understand their data needs and deliver integrated solutions.

• Identify high-value opportunities to apply AI to everyday engineering workflows including data discovery technical search map-data analysis validation support diagnostics release readiness incident triage and engineering productivity.

• Design and productionize knowledge-grounded Agentic AI solutions that can use approved documentation code metadata telemetry and operational knowledge to support multi-step engineering tasks.

• Help define the architecture and operating model for smart agents including retrieval tool use orchestration access controls evaluation observability human oversight and safe deployment.

• Create patterns that allow AI agents and data services to scale reliably in the cloud across environments and teams.

• Build reference implementations and reusable frameworks so teams can adopt cloud data and AI solutions without repeatedly solving the same foundational problems or creating unnecessary central dependencies.

• Lead architecture discussions design reviews and focused technical workshops across teams; clarify ownership boundaries and resolve cross-team technical seams.

• Mentor engineers through technical guidance design feedback code reviews and examples of strong engineering practices.

• Balance near-term delivery with long-term maintainability solution simplification security reliability and responsible use of AI.

• Bachelors 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.

• Demonstrated experience providing senior technical leadership across architecture design implementation and production operations.

• Strong experience with cloud-native and distributed systems including scalable services asynchronous or event-driven workflows data-intensive applications and reliability engineering.

• Hands-on experience with at least one major cloud platform such as 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 one or more languages such as 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.

• Demonstrated ability to influence technical direction across teams without relying on formal organizational authority.

• Strong written and verbal communication skills with the ability to explain complex technical decisions to both technical and non-technical stakeholders.

• Experience in automotive software-defined vehicles ADAS autonomous driving mapping geospatial systems robotics simulation or another safety- and scale-sensitive domain.

• Experience building or expanding mapping databases geospatial data platforms map-production pipelines map validation systems or data-delivery services.

• Experience with Azure Databricks Terraform Kubernetes Spark or PySpark Kafka or other event-streaming technologies and modern data-lake or lakehouse architectures.

• Experience with vector databases semantic search knowledge graphs metadata platforms document intelligence or knowledge-grounded AI applications.

• Experience designing and operating internal developer platforms engineering productivity tools or self-service cloud capabilities.

• Experience with model-training simulation offline analytics digital-twin or other high-volume data consumers.

• Experience defining AI quality security privacy governance and responsible-use practices for internal engineering tools.

• Experience scaling reusable engineering capabilities across multiple teams and managing tradeoffs among delivery speed performance reliability and cost.

• You are a builder who can move between architecture code infrastructure data and operational outcomes.

• You can distinguish a reusable engineering problem from a one-off team problem and focus effort where it creates the most leverage.

• You are comfortable working with ambiguity and turning emerging AI capabilities into reliable products with measurable adoption.

• You bring strong systems thinking: data quality security observability reliability cost and user experience are considered together.

• You communicate clearly create alignment and use influence rather than authority to drive adoption.

• You value practical delivery and can simplify complex technical choices without losing the long-term architectural direction.

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York Colorado California or Washington.
The salary range for this role: is $189300 to $290700. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.
Bonus Potential: An incentive pay program offers payouts based on company performance job level and individual performance.
Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical dental vision Health Savings Account Flexible Spending Accounts retirement savings plan sickness and accident benefits life insurance paid vacation & holidays tuition assistance programs employee assistance program GM vehicle discounts and more

About GM

Our vision is a world with Zero Crashes Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day individually and collectively to drive meaningful change through our words our deeds and our culture. Every day we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one were looking out for your well-beingat work and at homeso you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex race color national origin citizenship status religion age disability pregnancy or maternity status sexual orientation gender identity status as a veteran or protected veteran or any other similarly protected status in accordance with federal state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required where applicable to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment email us or call your email please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.