TN Visa Applied AI Engineer Jobs
Applied AI Engineer roles qualify for TN visa sponsorship under the USMCA's Computer Systems Analyst and Engineer categories. Canadian citizens can enter at the port of entry without a lottery wait. Mexican nationals follow the consular process. Your degree in computer science, AI, or a related engineering field is the core credential employers verify.
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Who We Are:
Bandwidth, a prior "Best of EC" award winner, is a global software company that helps enterprises deliver exceptional experiences through voice, messaging, and emergency services. Reaching 65+ countries and over 90 percent of the global economy, we're the only provider offering an owned communications cloud that delivers advanced automation, AI integrations, global reach, and premium human support. Bandwidth is trusted for mission-critical communications by the Global 2000, hyperscalers, and SaaS builders!
At Bandwidth, your music matters when you are part of the BAND. We celebrate differences and encourage BANDmates to be their authentic selves. #jointheband
What We Are Looking For:
As an Applied AI Engineer on the Corporate IT Engineering team, you'll identify where AI can create real leverage across our internal systems and operations, and build it. You'll work inside a team that owns a broad and complex infrastructure footprint, embedding AI into the platforms and workflows that keep Bandwidth running. This is an infrastructure and systems role with a deep AI focus.
What You'll Do:
- Own and extend existing AI platforms and tooling, improving reliability, expanding capabilities, and integrating them more deeply with internal systems.
- Architect and build internal API layers and shared services that allow AI workflows and internal applications to publish, version, and retrieve outputs across the engineering ecosystem.
- Identify and build AI-powered tooling that creates leverage across the Corporate IT Engineering stack, including infrastructure, identity, monitoring, and automation platforms.
- Develop and iterate on proof-of-concepts that demonstrate how AI can augment or automate internal workflows; from anomaly detection in infrastructure logs to AI-assisted documentation and IT troubleshooting.
- Containerize and orchestrate AI workloads using Docker and Kubernetes, ensuring reliable and reproducible deployments across environments.
- Automate infrastructure provisioning and configuration using Terraform and Ansible, following infrastructure-as-code best practices.
- Establish AI development patterns and best practices across the Corporate IT Engineering organization, helping teams adopt AI capabilities effectively and responsibly.
- Stay current with the evolving AI and MLOps landscape and bring relevant advancements back to the team.
What You Need:
- AI & Application Development
- Hands-on experience owning or extending LLM-powered platforms, including RAG pipeline development, prompt engineering, and integrating LLM APIs into production internal systems.
- Expert-level knowledge of AI infrastructure, including model serving, inference optimization, GPU/CPU resource management, and MLOps pipelines.
- Experience designing and building internal API layers or shared platform services that multiple teams and systems publish to and consume from.
- Proficiency in Python and/or TypeScript for building integrations, scripts, and lightweight internal services.
-
Experience working with REST APIs and building integrations across a diverse internal tooling ecosystem.
-
Cloud & Infrastructure
- Strong AWS experience: required proficiency in core services (EC2, ECS/EKS, S3, RDS, Lambda, IAM, VPC) and experience architecting and operating production workloads on AWS.
- Deep Docker and Kubernetes expertise: required hands-on experience containerizing applications, writing Dockerfiles, managing multi-container deployments, and orchestrating workloads with Kubernetes (EKS or self-managed).
- Deep Terraform and Ansible expertise: required experience writing and maintaining Terraform modules for cloud infrastructure, and using Ansible for configuration management and automation.
- Experience with GitHub for version control, pull request workflows, branching strategies, and CI/CD integration.
-
Experience with Artifactory for artifact management, including publishing and consuming build artifacts, Docker images, and package registries.
-
Mindset & Collaboration
- An experimental mindset: comfortable inheriting imperfect systems, iterating quickly, and improving as you go.
- Ability to evaluate AI capabilities through a business lens, understanding not just what's possible but what creates real value for internal teams and the organization.
- Strong communication skills and the ability to explain AI concepts and tradeoffs to non-technical stakeholders.
- A collaborative, team-first approach with a genuine curiosity about where AI is headed.
- A Bachelor's degree in Computer Science, Engineering, or equivalent hands-on experience.
Bonus Points:
- Experience with agentic frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
- Familiarity with corporate IT or infrastructure engineering environments, understanding how enterprise platforms around identity, monitoring, and automation operate.
- Background building MCP (Model Context Protocol) servers or tools that extend AI agent capabilities.
- Experience with vector databases (e.g., Pinecone, Weaviate, pgvector) and semantic search.
- Experience building or maintaining internal developer platforms, artifact registries, or shared API services.
The Whole Person Promise:
At Bandwidth, we're pretty proud of our corporate culture, which is rooted in our "Whole Person Promise." We promise all employees that they can have meaningful work AND a full life, and we provide a work environment geared toward enriching your body, mind, and spirit. How do we do that? Well…
- 100% company-paid Medical, Vision, & Dental coverage for you and your family with low deductibles and low out-of-pocket expenses.
- All new hires receive four weeks of PTO.
- PTO Embargo. When you take time off (of any kind!) you're embargoed from working. Bandmates and managers are not allowed to interrupt your PTO – not even with email.
- Additional PTO can be earned throughout the year through volunteer hours and Bandwidth challenges.
- "Mahalo moments" program grants additional time off for life's most important moments like graduations, buying a first home, getting married, wedding anniversaries (every five years), and the birth of a grandchild.
- 90-Minute Workout Lunches and unlimited meetings with our very own nutritionist.
Are you excited about the position and its responsibilities, but not sure if you're 100% qualified? Do you feel you can work to help us crush the mission? If you answered 'yes' to both of these questions, we encourage you to apply! You won't want to miss the opportunity to be a part of the BAND.
Applicant Privacy Notice

Who We Are:
Bandwidth, a prior "Best of EC" award winner, is a global software company that helps enterprises deliver exceptional experiences through voice, messaging, and emergency services. Reaching 65+ countries and over 90 percent of the global economy, we're the only provider offering an owned communications cloud that delivers advanced automation, AI integrations, global reach, and premium human support. Bandwidth is trusted for mission-critical communications by the Global 2000, hyperscalers, and SaaS builders!
At Bandwidth, your music matters when you are part of the BAND. We celebrate differences and encourage BANDmates to be their authentic selves. #jointheband
What We Are Looking For:
As an Applied AI Engineer on the Corporate IT Engineering team, you'll identify where AI can create real leverage across our internal systems and operations, and build it. You'll work inside a team that owns a broad and complex infrastructure footprint, embedding AI into the platforms and workflows that keep Bandwidth running. This is an infrastructure and systems role with a deep AI focus.
What You'll Do:
- Own and extend existing AI platforms and tooling, improving reliability, expanding capabilities, and integrating them more deeply with internal systems.
- Architect and build internal API layers and shared services that allow AI workflows and internal applications to publish, version, and retrieve outputs across the engineering ecosystem.
- Identify and build AI-powered tooling that creates leverage across the Corporate IT Engineering stack, including infrastructure, identity, monitoring, and automation platforms.
- Develop and iterate on proof-of-concepts that demonstrate how AI can augment or automate internal workflows; from anomaly detection in infrastructure logs to AI-assisted documentation and IT troubleshooting.
- Containerize and orchestrate AI workloads using Docker and Kubernetes, ensuring reliable and reproducible deployments across environments.
- Automate infrastructure provisioning and configuration using Terraform and Ansible, following infrastructure-as-code best practices.
- Establish AI development patterns and best practices across the Corporate IT Engineering organization, helping teams adopt AI capabilities effectively and responsibly.
- Stay current with the evolving AI and MLOps landscape and bring relevant advancements back to the team.
What You Need:
- AI & Application Development
- Hands-on experience owning or extending LLM-powered platforms, including RAG pipeline development, prompt engineering, and integrating LLM APIs into production internal systems.
- Expert-level knowledge of AI infrastructure, including model serving, inference optimization, GPU/CPU resource management, and MLOps pipelines.
- Experience designing and building internal API layers or shared platform services that multiple teams and systems publish to and consume from.
- Proficiency in Python and/or TypeScript for building integrations, scripts, and lightweight internal services.
-
Experience working with REST APIs and building integrations across a diverse internal tooling ecosystem.
-
Cloud & Infrastructure
- Strong AWS experience: required proficiency in core services (EC2, ECS/EKS, S3, RDS, Lambda, IAM, VPC) and experience architecting and operating production workloads on AWS.
- Deep Docker and Kubernetes expertise: required hands-on experience containerizing applications, writing Dockerfiles, managing multi-container deployments, and orchestrating workloads with Kubernetes (EKS or self-managed).
- Deep Terraform and Ansible expertise: required experience writing and maintaining Terraform modules for cloud infrastructure, and using Ansible for configuration management and automation.
- Experience with GitHub for version control, pull request workflows, branching strategies, and CI/CD integration.
-
Experience with Artifactory for artifact management, including publishing and consuming build artifacts, Docker images, and package registries.
-
Mindset & Collaboration
- An experimental mindset: comfortable inheriting imperfect systems, iterating quickly, and improving as you go.
- Ability to evaluate AI capabilities through a business lens, understanding not just what's possible but what creates real value for internal teams and the organization.
- Strong communication skills and the ability to explain AI concepts and tradeoffs to non-technical stakeholders.
- A collaborative, team-first approach with a genuine curiosity about where AI is headed.
- A Bachelor's degree in Computer Science, Engineering, or equivalent hands-on experience.
Bonus Points:
- Experience with agentic frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar.
- Familiarity with corporate IT or infrastructure engineering environments, understanding how enterprise platforms around identity, monitoring, and automation operate.
- Background building MCP (Model Context Protocol) servers or tools that extend AI agent capabilities.
- Experience with vector databases (e.g., Pinecone, Weaviate, pgvector) and semantic search.
- Experience building or maintaining internal developer platforms, artifact registries, or shared API services.
The Whole Person Promise:
At Bandwidth, we're pretty proud of our corporate culture, which is rooted in our "Whole Person Promise." We promise all employees that they can have meaningful work AND a full life, and we provide a work environment geared toward enriching your body, mind, and spirit. How do we do that? Well…
- 100% company-paid Medical, Vision, & Dental coverage for you and your family with low deductibles and low out-of-pocket expenses.
- All new hires receive four weeks of PTO.
- PTO Embargo. When you take time off (of any kind!) you're embargoed from working. Bandmates and managers are not allowed to interrupt your PTO – not even with email.
- Additional PTO can be earned throughout the year through volunteer hours and Bandwidth challenges.
- "Mahalo moments" program grants additional time off for life's most important moments like graduations, buying a first home, getting married, wedding anniversaries (every five years), and the birth of a grandchild.
- 90-Minute Workout Lunches and unlimited meetings with our very own nutritionist.
Are you excited about the position and its responsibilities, but not sure if you're 100% qualified? Do you feel you can work to help us crush the mission? If you answered 'yes' to both of these questions, we encourage you to apply! You won't want to miss the opportunity to be a part of the BAND.
Applicant Privacy Notice
See all 394+ Applied AI Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Applied AI Engineer roles.
Get Access To All JobsTips for Finding TN Visa Sponsorship as an Applied AI Engineer
Align your degree to the TN category
TN approval depends on your degree field matching the role's technical requirements. A computer science or electrical engineering degree supports an Applied AI Engineer filing more cleanly than a statistics degree alone, even if your work experience is identical.
Document your AI specialization before applying
Gather publications, patents, or project portfolios that demonstrate applied machine learning work specifically. Officers reviewing TN petitions want to see that your role involves engineering AI systems, not just using off-the-shelf tools.
Target employers experienced with visa sponsorship
Focus on companies with recent visa filings in tech and engineering roles. These employers have demonstrated experience with work visa sponsorship, which signals they understand visa processes and employment authorization. For TN status, you'll need an employer willing to write a support letter—your key document for port of entry presentation (Canadians) or consulate application (Mexicans). Companies with established visa sponsorship experience are more likely to be comfortable with this straightforward process. This gives you a concrete shortlist before you send a single application.
Use Migrate Mate to find TN-ready employers
Search Migrate Mate to identify Applied AI Engineer openings at companies already familiar with TN sponsorship. Filtering by visa type saves you from negotiating the basics with employers who have never navigated the process.
Confirm the employer's offer letter covers TN requirements
Your offer letter must state your job title, duties, salary, and employment start date in language that maps to the TN category. A vague letter describing general software work is one of the most common reasons TN applications get questioned at the border.
Understand how Mexican and Canadian filing paths differ
Canadian citizens can file at a U.S. port of entry the same day with the employer's support documents in hand. Mexican nationals must schedule a consular interview first, which adds lead time your employer needs to account for when setting your start date.
Applied AI Engineer jobs are hiring across the US. Find yours.
Find Applied AI Engineer JobsApplied AI Engineer TN Visa: Frequently Asked Questions
Does an Applied AI Engineer role qualify for TN visa status?
Yes, Applied AI Engineer positions typically qualify under the Computer Systems Analyst or Engineer categories in the USMCA TN classification, provided your job duties center on designing, developing, or deploying AI systems. The role must require a relevant bachelor's degree or higher, and your employer's offer letter needs to reflect duties that match one of those designated occupational categories.
How does TN visa sponsorship compare to H-1B for this role?
TN has no annual lottery and no cap for Canadian citizens, so you can start as soon as your employer is ready and your documents are in order. H-1B requires entering a random lottery each spring, with a wait of months even if selected. For Applied AI Engineers with Canadian or Mexican citizenship, TN is a faster and more predictable path to U.S. employment than the H-1B process.
What documents does my employer need to prepare for my TN application?
Your employer provides a support letter on company letterhead stating your job title, a description of duties tied to the qualifying TN category, your start date, and confirmation that the position requires a professional degree. You bring your degree credential, valid passport, and the support letter. USCIS does not adjudicate TN applications for Canadians; CBP officers review everything at the port of entry.
Where can I find Applied AI Engineer jobs that already support TN sponsorship?
Migrate Mate is built specifically for this search. You can filter openings by visa type to find Applied AI Engineer roles at companies that have sponsored TN visas before, which removes the uncertainty of approaching employers who have never handled the process. Starting your search there shortens the time between offer and filing.
Can I switch employers while on TN status as an Applied AI Engineer?
Yes, but your TN status is tied to your current employer. Before your last day, your new employer must have a support letter ready and you must obtain new TN authorization, either at a port of entry for Canadians or through a consular appointment for Mexican nationals. There is no USCIS transfer petition as with H-1B, so the timing of your transition matters.
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