H-1B Visa Solutions Architect Jobs
Solutions Architect roles qualify for H-1B visa sponsorship as specialty occupations requiring a bachelor's degree or higher in computer science, information systems, or a related field. Employers file the LCA with DOL before your H-1B petition, certifying the offered wage meets the prevailing wage for your work location.
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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 3,732+ H-1B Visa Solutions Architect Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Solutions Architect Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship in Solutions Architect
Align your degree to the role
USCIS evaluates whether your degree field directly relates to Solutions Architect duties. A computer science or engineering degree maps cleanly. An unrelated degree needs supporting evidence that your coursework or credentials qualify you for the specialty occupation.
Check LCA filings before applying
Use Migrate Mate to filter Solutions Architect roles by employers with active H-1B LCA filing history, so you're targeting companies that have already committed to the sponsorship process rather than guessing from job descriptions.
Verify the prevailing wage tier for your location
The DOL's OFLC Wage Search assigns Solutions Architect roles to wage levels based on experience and responsibility. Ask your prospective employer which wage level they're filing at, since Level I filings face heavier USCIS scrutiny for senior-scope roles.
Document your cloud architecture credentials
Gather AWS, Azure, or GCP certifications plus project portfolios before engaging employers. If USCIS issues an RFE questioning specialty occupation, documented technical credentials specific to solutions architecture strengthen the response significantly.
Negotiate premium processing into your offer
Solutions Architect hiring often moves on tight timelines tied to project kickoffs. Ask during negotiation whether the employer will file with premium processing, which gives USCIS a 15-business-day adjudication window rather than standard processing.
Clarify the start date against the cap year
H-1B employment can't begin before October 1 of the fiscal year for cap-subject petitions. If your offer letter names an earlier start date, you'll need to confirm how the employer handles the gap, either through a different status or a delayed start.
H-1B Visa Solutions Architect: Frequently Asked Questions
Does a Solutions Architect role qualify as a specialty occupation for H-1B purposes?
Yes. USCIS treats Solutions Architect as a specialty occupation because the role normally requires at least a bachelor's degree in computer science, information systems, or software engineering. Employers must document that the position's actual duties require that level of theoretical knowledge, not just experience. Roles scoped as generalist IT support rather than architecture design face higher scrutiny.
How do I find employers actively sponsoring H-1B visas for Solutions Architect positions?
Migrate Mate surfaces employers with verified LCA filing history for Solutions Architect roles, so you can see which companies have gone through the DOL certification process before you apply. Checking LCA filings is more reliable than reading job descriptions, since many postings don't explicitly state sponsorship availability.
Can I switch from OPT to H-1B status while working as a Solutions Architect?
Yes. Your employer files a cap-subject H-1B petition during the April registration window while you continue working on OPT. If your OPT expires before October 1, the cap-gap rule extends your work authorization automatically, provided you maintain F-1 status and your petition remains pending or approved.
What happens to my H-1B if my employer changes my job title or scope from Solutions Architect to a different role?
A material change in duties, location, or wage level requires an amended H-1B petition before the change takes effect. Moving from Solutions Architect to Engineering Manager, for example, triggers a new specialty occupation analysis. Failing to amend can create a period of unauthorized employment that affects future petitions and green card applications.
Do cloud certifications like AWS or Azure affect H-1B approval chances for Solutions Architect roles?
Certifications don't substitute for a qualifying degree, but they help in RFE responses. USCIS sometimes questions whether a specific job actually requires a specialty degree rather than general IT skills. AWS Solutions Architect, Azure Solutions Expert, or GCP Professional certifications, paired with degree credentials and a detailed job duties letter, reinforce the specialty occupation argument.