Senior Cloud Solutions Architect Jobs in USA with Visa Sponsorship
Senior Cloud Solutions Architects are among the most consistently sponsored roles in tech. Employers routinely file H-1B visa, L-1A, and O-1 visa petitions for this title, and the specialty occupation standard is straightforward to satisfy given the degree and technical requirements of the role. For detailed occupation requirements, see the O*NET profile.
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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 team’s 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.
The role
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 adopt—not from becoming the owner of every mapping system or every AI initiative.
What you’ll do
- 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.
Required Qualifications
- 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.
- 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.
Preferred Qualifications
- 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.
What will make you successful
- 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 $189,300 to $290,700. 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, we're looking out for your well-being–at work and at home–so 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 us at 1-800-865-7580. In 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.
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 team’s 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.
The role
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 adopt—not from becoming the owner of every mapping system or every AI initiative.
What you’ll do
- 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.
Required Qualifications
- 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.
- 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.
Preferred Qualifications
- 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.
What will make you successful
- 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 $189,300 to $290,700. 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, we're looking out for your well-being–at work and at home–so 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 us at 1-800-865-7580. In 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.
See all 20,693+ Senior Cloud Solutions Architect Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Senior Cloud Solutions Architect roles.
Get Access To All JobsTips for Finding Senior Cloud Solutions Architect Jobs
Target employers with an active H-1B filing history
Cloud architecture roles attract heavy H-1B sponsorship from AWS, Google Cloud, Microsoft Azure, and their enterprise clients. Companies with established immigration programs move faster and have dedicated legal teams, which meaningfully reduces approval timelines and administrative friction.
Certifications strengthen your specialty occupation case
AWS Certified Solutions Architect, Google Professional Cloud Architect, and Azure Solutions Architect Expert credentials signal domain-specific expertise. Consular officers and USCIS adjudicators view these alongside your degree when assessing whether the role meets the specialty occupation standard.
Clarify whether the role is consulting or direct employment
Cloud architects placed at third-party client sites face additional H-1B scrutiny under itinerant worker rules. Direct employment with the sponsoring company avoids this entirely. If consulting is the model, confirm the employer has experience managing end-client documentation requirements for RFE responses.
L-1A is a viable path if you have intracompany history
Multinationals frequently transfer senior cloud architects on L-1A visas, which bypass the H-1B cap entirely. If you've spent at least one year in a managerial or executive role at a foreign affiliate, this is worth raising directly with the hiring team during the offer stage.
Document your system design and architecture decisions in writing
USCIS requests for evidence on cloud architect petitions often focus on the degree of independent judgment required. Architecture decision records, design documents, and technical proposals that show you own architectural choices, not just implement them, form the strongest supporting evidence for approval.
Start the LCA process as early as possible with your employer
The Labor Condition Application must be certified by the Department of Labor before your H-1B petition can be filed. Employers unfamiliar with the timeline sometimes underestimate the lead time needed. Flag this in your first conversation with HR so the process starts without unnecessary delays.
Frequently Asked Questions
Does a Senior Cloud Solutions Architect role qualify as a specialty occupation for the H-1B?
Yes, reliably. USCIS consistently finds that senior cloud architecture roles meet the specialty occupation standard because the position normally requires at least a bachelor's degree in computer science, information systems, or a related engineering field. The role's complexity, independent judgment requirements, and technical depth all support this classification. RFEs are uncommon for senior-level architect titles compared to more generalist IT roles.
What degree fields satisfy H-1B requirements for this role?
Computer science, software engineering, information systems, electrical engineering, and related technical disciplines are the most straightforward fits. A degree in a non-technical field is unlikely to satisfy the specialty occupation requirement unless paired with substantial graduate-level coursework or certifications directly tied to cloud architecture. USCIS looks for a direct relationship between the degree field and the duties of the specific role.
How competitive is H-1B sponsorship for cloud architects compared to other tech roles?
Cloud architects fare well in sponsorship volume and approval rates. DOL disclosure data consistently shows cloud and solutions architect titles among the most frequently sponsored in the technology sector. The specialty occupation argument is strong, employers are highly motivated to sponsor at the senior level, and approval rates for this title are among the higher ones in the H-1B visa program.
Can I find Senior Cloud Solutions Architect roles with visa sponsorship confirmed upfront?
Yes. Migrate Mate lists cloud architecture roles from employers who have confirmed they sponsor work visas, so you're not applying blind and waiting to raise the question later. Filtering by sponsorship status saves significant time and avoids the awkward conversation where you find out at the offer stage that sponsorship isn't available.
Does an O-1A visa work for Senior Cloud Solutions Architects, and how hard is it to qualify?
O-1A is achievable for cloud architects with a strong record of distinction, but it requires more than seniority. Qualifying evidence typically includes industry awards, published technical work, speaking at recognized conferences, or compensation significantly above peers. Architects who have led high-profile migrations, hold widely cited patents, or are recognized as subject matter experts in the cloud community are the strongest candidates.
What is the prevailing wage requirement for sponsored Senior Cloud Solutions Architect jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.