Green Card AI Engineer Jobs
AI Engineer roles qualify for green card sponsorship under EB-2 for advanced-degree professionals and EB-3 for skilled workers with a bachelor's degree. Your employer files a PERM labor certification with DOL before petitioning USCIS, permanently sponsoring your U.S. residency rather than renewing a temporary work authorization every few years.
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Get Access To All JobsAWS AI/IoT Architect
Redapt Inc. is a pioneering world-class data center infrastructure integrator, technology engineering firm, and cloud services provider. Our teams focus on delivering innovative solutions and services that power our customers' most demanding applications and enable them to extract powerful insights from data that drive true business value. We are looking for a Senior AWS IoT Architect to join our Cloud Solutions team. This hands-on role will build and operate secure, multi-tenant IoT platforms on AWS, connecting embedded Linux devices and edge AI hardware to cloud services, and building and deploying generative AI solutions on AWS using Amazon Bedrock. Our engineers own implementation from device provisioning and on-device software through cloud integration, over-the-air updates, and fleet operations. You will work with cloud, embedded, and hardware teams to deliver reliable solutions and validate them on simulated fleets and physical development boards.
Responsibilities
- Design and implement AWS IoT Core solutions for device onboarding, connectivity, identity, fleet management, and tenant isolation, using per-device X.509 certificates, mutual TLS, fleet provisioning with claim certificates, certificate revocation, and AWS Private CA.
- Develop AWS IoT Greengrass v2 components, recipes, and deployments for both the Java nucleus and nucleus lite, including on resource-constrained devices, with recovery and state-management behavior suited to the device.
- Design, develop, test, and deploy AI applications using Amazon Bedrock foundation models and AWS services, including model invocation, inference settings, and integration through AWS SDKs.
- Build retrieval-augmented generation (RAG) solutions using Amazon Bedrock Knowledge Bases or custom retrieval pipelines, including ingestion, chunking, embeddings, vector stores and vector search, retrieval quality, grounding in enterprise data, and source citations.
- Implement AI agents and tool integrations that connect models to enterprise APIs and workflows, with schema validation, controlled execution, error handling, explicit permissions, and human approval where needed.
- Develop prompts and structured extraction workflows for document understanding, classification, summarization, and business process automation.
- Build Python services and APIs that integrate AI capabilities with customer applications, databases, and enterprise data sources.
- Create representative evaluation datasets and automated tests to measure accuracy, grounding, extraction quality, and agent task completion; validate changes before release.
- Implement layered AI safeguards using Amazon Bedrock Guardrails, IAM, encryption, data access controls, output validation, and protections against prompt injection.
- Build on-device agents in Python and C/C++ for embedded Linux, build board images with Yocto, integrate systemd services, and cross-compile and package software for Arm and other embedded targets.
- Implement secure OTA pipelines for applications, models, and supported firmware, with manifests signed using AWS KMS or AWS Signer, verification before installation, staged rollout, health checks, failure recovery, rollback, and anti-rollback controls.
- Manage static and dynamic thing groups and AWS IoT Jobs, including rollout rates, abort thresholds, retries, and fleet deployment status.
- Build MQTT telemetry pipelines, topic structures, versioned message schemas, and IoT rules that route data to streaming services and Amazon S3, including buffering, reconnect behavior, and duplicate-message handling.
- Test at fleet scale with containerized device simulators and real-board lab testing, covering load, connectivity, provisioning, OTA, and recovery; diagnose connectivity, interrupted updates, power-loss recovery, security, and device performance issues.
- Apply device security practices, including secure boot, debug-port lockdown, least-privilege IoT policies, and hardware-backed keys where the device supports them.
Skills You Bring With You
- Strong Python and software engineering skills, including API development, automated testing, debugging, code review, and maintainable application design.
- AWS IoT Device Management and AWS IoT Device Defender, including fleet indexing, secure tunneling, and audit checks.
- Knowledge and experience in developing tenant-aware AWS backend workflows with Lambda, Step Functions, EventBridge, and DynamoDB partition design for multi-tenant data, with tenant-scoped IAM and IoT policies.
- Practical experience with RAG, embeddings, vector stores, retrieval quality, and grounding responses in enterprise data, including Amazon Bedrock Knowledge Bases.
- Experience building agent workflows and tool calling, with schema validation, controlled execution, error handling, and integration with external systems.
Qualifications
- BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or a related field preferred; equivalent experience considered.
- 5+ years of experience in IoT, embedded software, cloud engineering, or related roles, with hands-on responsibility for production systems.
- Demonstrated delivery of AWS-connected device solutions spanning embedded Linux development, secure device lifecycle management, cloud integration, and production operations.
Additional Experience We Value
- Hailo AI processors and accelerators (Hailo-8, Hailo-10H, Hailo-15), including HailoRT, the Dataflow Compiler, and HEF artifacts.
- Microchip PolarFire SoC, including the VectorBlox SDK, VNNX artifacts, and the PolarFire security features.
- Hardware-backed device identity and key storage, including TPMs and secure elements such as Microchip ATECC608 or TA100, and approaches for devices with limited hardware key protection.
- Familiarity with EU Cyber Resilience Act requirements for security updates, vulnerability handling, and software bills of materials (SBOMs).
- Other IoT platforms, such as Avnet IoTConnect, and migration between IoT platforms.
- FPGA fundamentals, including secure bitstream packaging, deployment, compatibility validation, and recovery.
Travel Required
- Travel typically 5% or less a year
Equal Employment Opportunity
Redapt is an equal opportunity employer. Applicants will not be discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition, or any protected category prohibited by local, state, or federal laws. All employment is decided based on qualifications, merit, and business need.
AWS AI/IoT Architect
Redapt Inc. is a pioneering world-class data center infrastructure integrator, technology engineering firm, and cloud services provider. Our teams focus on delivering innovative solutions and services that power our customers' most demanding applications and enable them to extract powerful insights from data that drive true business value. We are looking for a Senior AWS IoT Architect to join our Cloud Solutions team. This hands-on role will build and operate secure, multi-tenant IoT platforms on AWS, connecting embedded Linux devices and edge AI hardware to cloud services, and building and deploying generative AI solutions on AWS using Amazon Bedrock. Our engineers own implementation from device provisioning and on-device software through cloud integration, over-the-air updates, and fleet operations. You will work with cloud, embedded, and hardware teams to deliver reliable solutions and validate them on simulated fleets and physical development boards.
Responsibilities
- Design and implement AWS IoT Core solutions for device onboarding, connectivity, identity, fleet management, and tenant isolation, using per-device X.509 certificates, mutual TLS, fleet provisioning with claim certificates, certificate revocation, and AWS Private CA.
- Develop AWS IoT Greengrass v2 components, recipes, and deployments for both the Java nucleus and nucleus lite, including on resource-constrained devices, with recovery and state-management behavior suited to the device.
- Design, develop, test, and deploy AI applications using Amazon Bedrock foundation models and AWS services, including model invocation, inference settings, and integration through AWS SDKs.
- Build retrieval-augmented generation (RAG) solutions using Amazon Bedrock Knowledge Bases or custom retrieval pipelines, including ingestion, chunking, embeddings, vector stores and vector search, retrieval quality, grounding in enterprise data, and source citations.
- Implement AI agents and tool integrations that connect models to enterprise APIs and workflows, with schema validation, controlled execution, error handling, explicit permissions, and human approval where needed.
- Develop prompts and structured extraction workflows for document understanding, classification, summarization, and business process automation.
- Build Python services and APIs that integrate AI capabilities with customer applications, databases, and enterprise data sources.
- Create representative evaluation datasets and automated tests to measure accuracy, grounding, extraction quality, and agent task completion; validate changes before release.
- Implement layered AI safeguards using Amazon Bedrock Guardrails, IAM, encryption, data access controls, output validation, and protections against prompt injection.
- Build on-device agents in Python and C/C++ for embedded Linux, build board images with Yocto, integrate systemd services, and cross-compile and package software for Arm and other embedded targets.
- Implement secure OTA pipelines for applications, models, and supported firmware, with manifests signed using AWS KMS or AWS Signer, verification before installation, staged rollout, health checks, failure recovery, rollback, and anti-rollback controls.
- Manage static and dynamic thing groups and AWS IoT Jobs, including rollout rates, abort thresholds, retries, and fleet deployment status.
- Build MQTT telemetry pipelines, topic structures, versioned message schemas, and IoT rules that route data to streaming services and Amazon S3, including buffering, reconnect behavior, and duplicate-message handling.
- Test at fleet scale with containerized device simulators and real-board lab testing, covering load, connectivity, provisioning, OTA, and recovery; diagnose connectivity, interrupted updates, power-loss recovery, security, and device performance issues.
- Apply device security practices, including secure boot, debug-port lockdown, least-privilege IoT policies, and hardware-backed keys where the device supports them.
Skills You Bring With You
- Strong Python and software engineering skills, including API development, automated testing, debugging, code review, and maintainable application design.
- AWS IoT Device Management and AWS IoT Device Defender, including fleet indexing, secure tunneling, and audit checks.
- Knowledge and experience in developing tenant-aware AWS backend workflows with Lambda, Step Functions, EventBridge, and DynamoDB partition design for multi-tenant data, with tenant-scoped IAM and IoT policies.
- Practical experience with RAG, embeddings, vector stores, retrieval quality, and grounding responses in enterprise data, including Amazon Bedrock Knowledge Bases.
- Experience building agent workflows and tool calling, with schema validation, controlled execution, error handling, and integration with external systems.
Qualifications
- BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or a related field preferred; equivalent experience considered.
- 5+ years of experience in IoT, embedded software, cloud engineering, or related roles, with hands-on responsibility for production systems.
- Demonstrated delivery of AWS-connected device solutions spanning embedded Linux development, secure device lifecycle management, cloud integration, and production operations.
Additional Experience We Value
- Hailo AI processors and accelerators (Hailo-8, Hailo-10H, Hailo-15), including HailoRT, the Dataflow Compiler, and HEF artifacts.
- Microchip PolarFire SoC, including the VectorBlox SDK, VNNX artifacts, and the PolarFire security features.
- Hardware-backed device identity and key storage, including TPMs and secure elements such as Microchip ATECC608 or TA100, and approaches for devices with limited hardware key protection.
- Familiarity with EU Cyber Resilience Act requirements for security updates, vulnerability handling, and software bills of materials (SBOMs).
- Other IoT platforms, such as Avnet IoTConnect, and migration between IoT platforms.
- FPGA fundamentals, including secure bitstream packaging, deployment, compatibility validation, and recovery.
Travel Required
- Travel typically 5% or less a year
Equal Employment Opportunity
Redapt is an equal opportunity employer. Applicants will not be discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition, or any protected category prohibited by local, state, or federal laws. All employment is decided based on qualifications, merit, and business need.
See all 3,707+ Green Card AI Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Green Card AI Engineer Jobs.
Get Access To All JobsTips for Finding Green Card Sponsorship as an AI Engineer
Document your AI specialization precisely
PERM requires your employer to define a specific job requirement, so gather transcripts, publications, and project portfolios that tie your ML, NLP, or computer vision expertise to a clearly bounded specialty occupation before the labor certification begins.
Target employers with active PERM filing history
Search Migrate Mate to filter AI Engineer roles by employers who have sponsored green cards before. A history of PERM filings signals an in-house process, reducing the delays that come from employers navigating sponsorship for the first time.
Clarify EB-2 versus EB-3 with your prospective employer
If your role requires an advanced degree or a specialized research background, push for EB-2 classification, which opens the National Interest Waiver path. Many AI Engineering roles qualify but get filed under EB-3 by default because employers use standard job description templates.
Verify the posted salary covers prevailing wage before signing
PERM requires DOL to certify that your offered wage meets or exceeds the prevailing wage for your role and location. Cross-check the offer against the OFLC Wage Search before accepting, because a wage shortfall forces your employer to restart the labor certification.
Ask employers about priority date strategy during interviews
Priority dates for India-born and China-born AI Engineers can mean multi-year waits at the EB-2 and EB-3 levels. Ask whether your employer files concurrently or immediately, and whether they use premium processing on the I-140 to lock in your priority date faster.
Align your O*NET job zone classification with USCIS standards
AI Engineer roles are classified in Job Zone 4 or 5 on O*NET, which supports specialty occupation arguments. Confirm that your employer's PERM job description references degree requirements consistent with that classification so USCIS approves the I-140 without a Request for Evidence.
Green Card AI Engineer: Frequently Asked Questions
Does my AI Engineer role qualify for EB-2 or EB-3 green card sponsorship?
Most AI Engineer positions qualify for EB-2 when the role requires a master's degree or equivalent in computer science, machine learning, or a related field. If the employer requires only a bachelor's degree, EB-3 applies instead. Your employer's PERM labor certification must accurately reflect the minimum educational requirement the role genuinely needs, not just what you personally hold.
How does PERM green card sponsorship differ from H-1B for AI Engineers?
H-1B visa is a temporary, renewable status tied to an employer and subject to an annual lottery. PERM sponsorship leads to permanent residency and has no lottery at the EB-3 level. The tradeoff is timeline: PERM labor certification, I-140 approval, and adjustment of status together take several years, compared to H-1B status that can begin within months of a cap-subject approval.
Which employers sponsor green cards for AI Engineers?
Large technology companies, AI-focused research labs, financial institutions running quantitative or risk modeling teams, and healthcare analytics firms regularly sponsor EB-2 and EB-3 green cards for AI Engineers. You can search Migrate Mate to filter AI Engineer roles specifically by employers with PERM filing history, narrowing your search to companies already familiar with the sponsorship process.
What happens to my green card case if I change employers mid-process?
Changing employers before your I-140 is approved generally requires restarting PERM with the new employer. After I-140 approval and once your priority date is current, the AC21 portability rule lets you transfer your case to a new employer offering a same or similar role without losing your priority date, which matters most for nationals of countries with long backlogs.
Can I self-petition for a green card as an AI Engineer without employer sponsorship?
Yes, if you have strong credentials. The EB-2 National Interest Waiver lets you self-petition without an employer or PERM labor certification if you can demonstrate your work in AI benefits the United States beyond your direct employer. Researchers publishing in peer-reviewed venues, contributors to open-source infrastructure, or specialists working on national security applications are common successful NIW petitioners in this field. Use Migrate Mate to identify roles at employers who also support NIW filings alongside traditional PERM.