Green Card AI Architect Jobs
AI Architect roles qualify for EB-2 green card sponsorship when the position requires an advanced degree in computer science, machine learning, or a related field. Employers file a PERM labor certification with the DOL before sponsoring you permanently. Most AI Architect positions satisfy specialty occupation standards, making direct sponsorship through the EB-2 category a realistic path.
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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 905+ Green Card AI Architect Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Green Card AI Architect Jobs.
Get Access To All JobsTips for Finding Green Card Sponsorship in AI Architect
Document your AI architecture credentials strategically
Gather transcripts, publications, patents, and performance reviews before applying. PERM requires your employer to prove no qualified U.S. worker is available, so your credentials need to clearly distinguish you from the domestic candidate pool for an AI Architect role.
Target employers with active PERM filing history
Not every tech company runs green card sponsorship programs. Search OFLC's public disclosure data for employers who have filed PERM applications for AI or machine learning architect roles specifically, not just software engineers generally.
Verify your role qualifies under EB-2 not just EB-3
If the job posting requires a master's degree or equivalent, push for EB-2 classification upfront. EB-2 skips the supervised recruitment period that can stall EB-3 cases and generally reflects better on your long-term residency timeline.
Search for sponsoring employers using Migrate Mate
Use Migrate Mate to filter AI Architect openings by employers who have sponsored green cards before. That history signals a company already understands PERM timelines and won't abandon your petition mid-process due to unfamiliarity.
Negotiate PERM start timing before accepting an offer
Ask your prospective employer whether they start the PERM process within the first year of employment or only after a probationary period. Delays of 18 to 24 months before filing are common and can significantly push back your priority date.
Align your O*NET occupation code with your actual duties
PERM applications reference O*NET codes to define the role. If your duties span AI research and infrastructure architecture, ensure your employer files under the code that best matches your day-to-day work, not simply the most convenient title.
Green Card AI Architect: Frequently Asked Questions
Does an AI Architect role typically qualify for EB-2 green card sponsorship?
Yes. AI Architect positions almost always require at least a bachelor's degree in computer science, artificial intelligence, or a closely related field, and most employers specify a master's degree or higher. That degree requirement makes the role eligible for EB-2 classification, which covers advanced-degree professionals. Your employer files a PERM labor certification with the DOL to begin the process.
How does the PERM green card process differ from H-1B sponsorship for an AI Architect?
H-1B visa sponsorship is temporary, capped at 85,000 per year, and subject to a lottery. Green card sponsorship through PERM has no annual cap at the EB-3 level for many countries and leads to permanent residency. The tradeoff is timeline: PERM requires a DOL-supervised recruitment process that typically adds six to eighteen months before USCIS even receives your I-140 petition.
How can I find AI Architect jobs where employers are already willing to sponsor a green card?
The most direct approach is filtering for employers with a documented PERM filing history. Migrate Mate lets you search AI Architect openings specifically filtered by employers who have sponsored employment-based green cards before, which removes the guesswork of approaching companies that have never run a PERM case.
What makes the PERM labor certification stage difficult for AI Architect candidates?
The DOL requires your employer to demonstrate that no qualified U.S. worker is available for the position. For AI Architect roles, this means running a tightly defined recruitment campaign where the job description must match your actual duties precisely. If the posted requirements are too broad, a U.S. applicant may technically qualify, and the PERM can be denied even if you're the stronger candidate.
Can my employer start the PERM process while I'm on an H-1B?
Yes, and doing so early is strategically important. Filing PERM while you're on H-1B lets you accrue a priority date before your temporary status expires. USCIS allows H-1B extensions beyond the standard six-year limit once your I-140 is approved or your PERM has been pending for 365 days, protecting your ability to stay in the U.S. while your green card processes.