E-3 Visa Cloud Engineer Jobs
Cloud Engineer roles in the U.S. qualify as E-3 visa specialty occupations, making them a strong fit for Australian professionals seeking visa sponsorship. The E-3 has no lottery and renews every two years, so you can build a long-term cloud career in the U.S. without the H-1B visa cap risk.
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The Cloud Engineer will design, build, and operate infrastructure and applications supporting UCLA Health’s Analytics Platform across both on-premises and multi-cloud environments (AWS, Azure, GCP).
This role focuses on enabling secure, scalable AI/ML and GenAI platforms, with an emphasis on automation, reliability, and compliance in a regulated healthcare setting.
Key Responsibilities
- Design, implement, and manage cloud and hybrid infrastructure supporting analytics and AI/ML workloads
- Build and operate MLOps capabilities, including:
- Model training and inference platforms
- Model and artifact management
- CI/CD and deployment pipelines
- Observability and monitoring solutions
- Cost optimization controls
- Develop and maintain automation and infrastructure-as-code (IaC) solutions for provisioning and configuration
- Troubleshoot and resolve complex system and environment issues across cloud and on-prem platforms
- Establish platform guardrails to ensure secure, reliable, and compliant operations
- Collaborate with cross-functional teams to:
- Gather requirements
- Design and prototype solutions
- Implement and test deployments
- Support ongoing operations and enhancements
- Apply security, privacy, and governance controls aligned with healthcare data regulations
- Execute release, deployment, and configuration management processes
What You’ll Bring
- Strong background in cloud engineering and platform operations
- Experience with multi-cloud environments (AWS, Azure, GCP)
- Proficiency in:
- Automation, scripting, and infrastructure-as-code
- CI/CD pipeline development and optimization
- Monitoring and observability tools
- Experience supporting AI/ML or data platform workloads (preferred)
- Ability to troubleshoot complex systems and drive solutions independently
- Strong collaboration skills and the ability to translate business requirements into technical solutions
Salary Range: $128500 - $298100 annually.
Qualifications
BS/MS in Computer Science (or equivalent)
AWS Certified Cloud Engineer, Architect, Administrator Certifications required
7+ years of advanced knowledge and experience as an AWS Cloud Engineer in all core services and offerings. AWS experience a plus
15+ years of advanced knowledge and experience of Microsoft Technologies such as, Windows server and Linux based servers, enterprise system support experience and strong background in systems engineering and administration for both operating systems
15+ years of advanced knowledge and experience with enterprise scale Windows technologies such as Server platforms, Desktop platforms, Exchange Environments, Active Directory, IIS, Windows Clustering, Virtualization and Collaboration tools. AWS Certification or equivalent experience preferred
Working knowledge of DevOps-like work or experience in a real time operational role
Advanced knowledge of analytics and AI/ML platform services across AWS, Azure, and GCP (e.g., AWS SageMaker/Bedrock, Azure Machine Learning/Azure OpenAI, Google Vertex AI) and how to operate them securely at enterprise scale.
Experience enabling teams to build and deploy ML/AI solutions by providing reusable platform capabilities (reference architectures, templates, SDK/CLI standards, self-service onboarding, and guardrails) rather than only project-specific implementations.
Hands-on experience operationalizing ML/AI workloads on cloud platforms (AWS/Azure/GCP): managed training/inference, batch vs real-time serving, feature/metadata management, model registry, and cost/performance optimization.
Strong MLOps/platform engineering experience: CI/CD for ML and GenAI, automated validation gates, reproducible pipelines, environment promotion, artifact/version management, and production monitoring (drift, data quality, latency, cost) using cloud-native and/or enterprise tooling (e.g., Azure DevOps/GitHub Actions, SageMaker Pipelines, Vertex AI Pipelines, MLflow, Terraform).
GenAI platform experience (AWS/Azure/GCP): deploying and governing LLM applications using managed services (e.g., Bedrock/Azure OpenAI/Vertex AI), RAG architectures, embeddings and vector databases/search, prompt/version management, and evaluation/guardrails for safety and groundedness.
Responsible AI + governance experience for regulated environments: PHI/PII protections, access controls, encryption and key management, audit logging, model/endpoint risk assessments, bias/fairness considerations, and policy enforcement aligned to HIPAA and secure SDLC.
Strong data engineering foundations that support AI platforms: standardized data ingestion/ETL/ELT, data quality/lineage, dataset and feature pipeline design, schema/version management, and integration with lake/lakehouse platforms (e.g., S3/ADLS/GCS with Spark/Databricks/BigQuery/Synapse) for feature and training data readiness.
Experience operating scalable training/inference platforms (GPU/accelerated workloads): capacity planning/quotas, cluster or managed compute configuration, distributed training concepts, performance tuning, and chargeback/showback in cloud environments.
Description
The Cloud Engineer will design, build, and operate infrastructure and applications supporting UCLA Health’s Analytics Platform across both on-premises and multi-cloud environments (AWS, Azure, GCP).
This role focuses on enabling secure, scalable AI/ML and GenAI platforms, with an emphasis on automation, reliability, and compliance in a regulated healthcare setting.
Key Responsibilities
- Design, implement, and manage cloud and hybrid infrastructure supporting analytics and AI/ML workloads
- Build and operate MLOps capabilities, including:
- Model training and inference platforms
- Model and artifact management
- CI/CD and deployment pipelines
- Observability and monitoring solutions
- Cost optimization controls
- Develop and maintain automation and infrastructure-as-code (IaC) solutions for provisioning and configuration
- Troubleshoot and resolve complex system and environment issues across cloud and on-prem platforms
- Establish platform guardrails to ensure secure, reliable, and compliant operations
- Collaborate with cross-functional teams to:
- Gather requirements
- Design and prototype solutions
- Implement and test deployments
- Support ongoing operations and enhancements
- Apply security, privacy, and governance controls aligned with healthcare data regulations
- Execute release, deployment, and configuration management processes
What You’ll Bring
- Strong background in cloud engineering and platform operations
- Experience with multi-cloud environments (AWS, Azure, GCP)
- Proficiency in:
- Automation, scripting, and infrastructure-as-code
- CI/CD pipeline development and optimization
- Monitoring and observability tools
- Experience supporting AI/ML or data platform workloads (preferred)
- Ability to troubleshoot complex systems and drive solutions independently
- Strong collaboration skills and the ability to translate business requirements into technical solutions
Salary Range: $128500 - $298100 annually.
Qualifications
BS/MS in Computer Science (or equivalent)
AWS Certified Cloud Engineer, Architect, Administrator Certifications required
7+ years of advanced knowledge and experience as an AWS Cloud Engineer in all core services and offerings. AWS experience a plus
15+ years of advanced knowledge and experience of Microsoft Technologies such as, Windows server and Linux based servers, enterprise system support experience and strong background in systems engineering and administration for both operating systems
15+ years of advanced knowledge and experience with enterprise scale Windows technologies such as Server platforms, Desktop platforms, Exchange Environments, Active Directory, IIS, Windows Clustering, Virtualization and Collaboration tools. AWS Certification or equivalent experience preferred
Working knowledge of DevOps-like work or experience in a real time operational role
Advanced knowledge of analytics and AI/ML platform services across AWS, Azure, and GCP (e.g., AWS SageMaker/Bedrock, Azure Machine Learning/Azure OpenAI, Google Vertex AI) and how to operate them securely at enterprise scale.
Experience enabling teams to build and deploy ML/AI solutions by providing reusable platform capabilities (reference architectures, templates, SDK/CLI standards, self-service onboarding, and guardrails) rather than only project-specific implementations.
Hands-on experience operationalizing ML/AI workloads on cloud platforms (AWS/Azure/GCP): managed training/inference, batch vs real-time serving, feature/metadata management, model registry, and cost/performance optimization.
Strong MLOps/platform engineering experience: CI/CD for ML and GenAI, automated validation gates, reproducible pipelines, environment promotion, artifact/version management, and production monitoring (drift, data quality, latency, cost) using cloud-native and/or enterprise tooling (e.g., Azure DevOps/GitHub Actions, SageMaker Pipelines, Vertex AI Pipelines, MLflow, Terraform).
GenAI platform experience (AWS/Azure/GCP): deploying and governing LLM applications using managed services (e.g., Bedrock/Azure OpenAI/Vertex AI), RAG architectures, embeddings and vector databases/search, prompt/version management, and evaluation/guardrails for safety and groundedness.
Responsible AI + governance experience for regulated environments: PHI/PII protections, access controls, encryption and key management, audit logging, model/endpoint risk assessments, bias/fairness considerations, and policy enforcement aligned to HIPAA and secure SDLC.
Strong data engineering foundations that support AI platforms: standardized data ingestion/ETL/ELT, data quality/lineage, dataset and feature pipeline design, schema/version management, and integration with lake/lakehouse platforms (e.g., S3/ADLS/GCS with Spark/Databricks/BigQuery/Synapse) for feature and training data readiness.
Experience operating scalable training/inference platforms (GPU/accelerated workloads): capacity planning/quotas, cluster or managed compute configuration, distributed training concepts, performance tuning, and chargeback/showback in cloud environments.
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Get Access To All JobsTips for Finding E-3 Visa Sponsorship as a Cloud Engineer
Align your credentials to U.S. cloud roles
Australian AWS, Azure, and GCP certifications are recognised by U.S. employers, but your degree transcript needs to show a computing or engineering field. A three-year Australian bachelor's degree satisfies the E-3 specialty occupation requirement when the field directly matches the role.
Target employers with active LCA filing history
Search the DOL's Office of Foreign Labor Certification disclosure data for companies that have filed LCAs for cloud or infrastructure roles. Employers already familiar with the LCA process move faster and are less likely to stall at the sponsorship conversation.
Raise E-3 sponsorship before the offer stage
Cloud engineering roles at mid-size tech companies often have hiring managers who conflate E-3 with H-1B. Clarifying upfront that the E-3 has no lottery, no employer quota, and a two-to-four week LCA turnaround removes the most common objection before it becomes a deal-breaker.
Use Migrate Mate's E-3 filing service after your offer
Once you have a signed offer, use Migrate Mate's E-3 filing service to handle your LCA submission, DS-160, and consulate preparation. This is where most applicants lose time trying to coordinate between the employer's HR team and a general immigration lawyer unfamiliar with E-3.
Confirm your role qualifies as specialty occupation
Not all cloud titles qualify automatically. A role listed as 'Cloud Support Technician' may not meet the USCIS specialty occupation threshold, while 'Cloud Infrastructure Engineer' or 'DevOps Engineer' typically does. Check that the job description requires a bachelor's degree in a specific technical field, not just any degree.
Prepare for consulate questions on remote work arrangements
If your cloud role is remote or hybrid, U.S. consular officers may ask about your primary worksite location, which must appear on your certified LCA. Make sure your employer has designated a specific U.S. office or address on the filing before your interview.
E-3 Visa Cloud Engineer: Frequently Asked Questions
How do I find Cloud Engineer jobs with E-3 visa sponsorship?
Migrate Mate lets you search Cloud Engineer roles filtered by E-3 visa sponsorship, so you're only seeing employers who have indicated they can support the process. Most general job platforms don't filter by visa type, which means you can spend weeks on roles that won't proceed. Migrate Mate removes that friction from the search.
How much does it cost to get an E-3 visa?
Migrate Mate's E-3 filing service covers the entire process for $499, including the Labor Condition Application, visa document preparation, and consulate appointment guidance. Traditional immigration lawyers charge $2,000–$5,000+ for the same work. The E-3 has less paperwork than most work visas, so paying thousands for legal help is usually unnecessary.
Does a Cloud Engineer role qualify as a specialty occupation for the E-3?
Cloud Engineer roles almost always qualify, provided the position requires a bachelor's degree or higher in computer science, information technology, or a closely related engineering field. The USCIS specialty occupation standard requires the degree to be specific to the role, not just any degree. Titles like Cloud Infrastructure Engineer, Cloud Architect, and DevOps Engineer consistently meet this threshold. Generic titles such as IT Generalist or Cloud Support Specialist carry more risk and may require additional documentation.
How does the E-3 compare to the H-1B for Cloud Engineer roles?
For Australian cloud engineers, the E-3 is a meaningfully different path. There's no annual lottery, no cap on available visas, and the LCA process typically certifies within seven to ten business days. H-1B registration opens once a year in March and selection is random, which means you can meet every requirement and still not get a slot. The E-3 lets you start when you have an offer, not when the lottery allows it.
Can I switch cloud employers after my E-3 is approved?
Yes, but the E-3 is employer-specific, so your new employer needs to file a fresh LCA and you'll need to attend a new consulate appointment before starting the role. You can't transfer the existing visa to a new employer the way some other visa categories allow. The process typically takes three to six weeks from offer to approval, assuming your new role also qualifies as a specialty occupation.